Asymptotic enumeration and limit laws of planar graphs

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统计软件中常见词汇的中英对照

统计软件中常见词汇的中英对照

统计软件词汇Absolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additive Noise, 加性噪声Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alpha factoring,α因子法Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis Of Effects, 效应分析Analysis Of Variance, 方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOVA (analysis of variance), 方差分析ANOVA Models, 方差分析模型ANOVA table and eta, 分组计算方差分析Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area 区域图Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差 ARIMA, 季节和非季节性单变量模型的极大似然估计 Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Collinearity, 共线性Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照, 质量控制图Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation, 相关性Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Crosstabs 列联表分析Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve Estimation, 曲线拟合Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量 Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Direct Oblimin, 斜交旋转Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法 Error Bar, 均值相关区间图Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量 Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explained variance (已说明方差)Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查Generalized least squares, 综合最小平方法GENLOG (Generalized liner models), 广义线性模型 Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型 Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点High-Low, 低区域图Higher Order Interaction Effects,高阶交互作用HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究 Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Image factoring,, 多元回归法Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K-Means Cluster逐步聚类分析K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least Squared Criterion,最小二乘方准则Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Leveage Correction,杠杆率校正Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形MSC(多元散射校正)Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal P-P, 正态概率分布图Normal Q-Q, 正态概率单位分布图Normal ranges, 正常范围Normal value, 正常值Normalization 归一化Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关 Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Pareto, 直条构成线图(又称佩尔托图)Partial correlation, 偏相关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式PCA(主成分分析)Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 构成图,饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡PLS(偏最小二乘法)Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal axis factoring,主轴因子法Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Profile trace, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling, 按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 接受域Regression coefficient, 回归系数Regression sum of square, 回归平方和 Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方和residual variance (剩余方差) Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system ), SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型 Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequence, 普通序列图Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significant Level, 显著水平Significance test, 显著性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单相关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层(复数)Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Test(检验)Test of linearity, 线性检验Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Two sided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α错误Type II error, 二类错误/β错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Unweighted least squares, 未加权最小平方法Upper limit, 上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方和Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W估计量W-estimation of location, 位置W估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z检验Zero correlation, 零相关Z-transformation, Z变换。

统计学专业英语词汇完整版(可编辑修改word版)

统计学专业英语词汇完整版(可编辑修改word版)

统计学专业英语词汇AAbsolute deviation,绝对离差Absolute number,绝对数Absolute residuals,绝对残差Acceleration array,加速度立体阵Acceleration in an arbitrary direction,任意方向上的加速度Acceleration normal,法向加速度Acceleration space dimension,加速度空间的维数Acceleration tangential,切向加速度Acceleration vector,加速度向量Acceptable hypothesis,可接受假设Accumulation,累积Accuracy,准确度Actual frequency,实际频数Adaptive estimator,自适应估计量Addition,相加Addition theorem,加法定理Additivity,可加性Adjusted rate,调整率Adjusted value,校正值Admissible error,容许误差Aggregation,聚集性Alternative hypothesis,备择假设Among groups,组间Amounts,总量Analysis of correlation,相关分析Analysis of covariance,协方差分析Analysis of regression,回归分析Analysis of time series,时间序列分析Analysis of variance,方差分析Angular transformation,角转换ANOVA(analysis of variance),方差分析ANOVA Models,方差分析模型Arcing,弧/弧旋Arcsine transformation,反正弦变换Area under the curve,曲线面积AREG,评估从一个时间点到下一个时间点回归相关时的误差ARIMA,季节和非季节性单变量模型的极大似然估计Arithmetic grid paper,算术格纸Arithmetic mean,算术平均数Arrhenius relation,艾恩尼斯关系Assessing fit,拟合的评估Associative laws,结合律Asymmetric distribution,非对称分布Asymptotic bias,渐近偏倚Asymptotic efficiency,渐近效率Asymptotic variance,渐近方差Attributable risk,归因危险度Attribute data,属性资料Attribution,属性Autocorrelation,自相关Autocorrelation of residuals,残差的自相关Average,平均数Average confidence interval length,平均置信区间长度Average growth rate,平均增长率BBar chart,条形图Bar graph,条形图Base period,基期Bayes theorem, 贝叶斯定理Bell-shaped curve,钟形曲线Bernoullidistribution,伯努力分布Best-trim estimator,最好切尾估计量Bias,偏性Binary logistic regression,二元逻辑斯蒂回归Binomial distribution,二项分布Bisquare,双平方Bivariate Correlate,二变量相关Bivariate normal distribution,双变量正态分布Bivariate normal population,双变量正态总体Biweight interval,双权区间Biweight M-estimator,双权M 估计量Block,区组/配伍组BMDP(Biomedical computer programs),BMDP 统计软件包Box plots,箱线图/箱尾图Break down bound,崩溃界/崩溃点CCanonical correlation,典型相关Caption,纵标目Case-control study,病例对照研究Categorical variable,分类变量Catenary,悬链线Cauchy distribution,柯西分布Cause-and-effect relationship,因果关系Cell,单元Censoring,终检Center of symmetry,对称中心Centering and scaling,中心化和定标Central tendency,集中趋势Central value,中心值CHAID-χ2AutomaticInteractionDetector,卡方自动交互检测Chance,机遇Chance error,随机误差Chance variable,随机变量Characteristic equation,特征方程Characteristic root,特征根Characteristic vector,特征向量Chebshev criterion of fit,拟合的切比雪夫准则Chernoff faces,切尔诺夫脸谱图Chi-square test,卡方检验/χ2 检验Choleskey decomposition,乔洛斯基分解Circle chart,圆图Class interval,组距Class mid-value,组中值Class upper limit,组上限Classified variable,分类变量Cluster analysis,聚类分析Cluster sampling,整群抽样Code,代码Coded data,编码数据Coding,编码Coefficient of contingency,列联系数Coefficientof determination,决定系数Coefficient ofmultiple correlation,多重相关系数Coefficient ofpartial correlation,偏相关系数Coefficient of production-moment correlation,积差相关系数Coefficient of rank correlation,等级相关系数Coefficient of regression,回归系数Coefficient of skewness,偏度系数Coefficient of variation,变异系数Cohort study,队列研究Column,列Column effect,列效应Column factor,列因素Combination pool,合并Combinative table,组合表Common factor,共性因子Common regression coefficient,公共回归系数Common value,共同值Common variance,公共方差Common variation,公共变异Communality variance,共性方差Comparability,可比性Comparison of bathes,批比较Comparison value,比较值Compartment model,分部模型Compassion,伸缩Complement of an event,补事件Complete association,完全正相关Complete dissociation,完全不相关Complete statistics,完备统计量Completely randomized design,完全随机化设计Composite event,联合事件/复合事件Concavity,凹性Conditional expectation,条件期望Conditional likelihood,条件似然Conditional probability,条件概率Conditionally linear,依条件线性Confidence interval,置信区间Confidence limit,置信限Confidence lower limit,置信下限Confidence upper limit,置信上限Confirmatory Factor Analysis,验证性因子分析Confirmatory research,证实性实验研究Confounding factor,混杂因素Conjoint,联合分析Consistency,相合性Consistency check,一致性检验Consistent asymptotically normal estimate,相合渐近正态估计Consistent estimate,相合估计Constrained nonlinear regression,受约束非线性回归Constraint,约束Contaminated distribution,污染分布Contaminated Gausssian,污染高斯分布Contaminated normal distribution,污染正态分布Contamination,污染Contamination model,污染模型Contingency table,列联表Contour,边界线Contribution rate,贡献率Control,对照Controlled experiments,对照实验Conventional depth,常规深度Convolution,卷积Corrected factor,校正因子Corrected mean,校正均值Correction coefficient,校正系数Correctness,正确性Correlation coefficient,相关系数Correlation index,相关指数Correspondence, 对应Counting,计数Counts,计数/频数Covariance,协方差Covariant,共变Cox Regression, Cox 回归Criteria for fitting,拟合准则Criteria of least squares,最小二乘准则Critical ratio,临界比Critical region,拒绝域Critical value,临界值Cross-over design,交叉设计Cross-section analysis,横断面分析Cross-section survey,横断面调查Cross tabs,交叉表Cross-tabulation table,复合表Cube root,立方根Cumulative distribution function,累计分布函数Cumulative probability,累计概率Curvature,曲率/弯曲Curve fit,曲线拟和Curve fitting,曲线拟合Curvilinear regression,曲线回归Curvilinear relation,曲线关系Cut-and-try method,尝试法Cycle,周期Cyclist,周期性DD test, D 检验Data acquisition,资料收集Databank,数据库Data capacity,数据容量Data deficiencies,数据缺乏Data handling,数据处理Data manipulation,数据处理Data processing,数据处理Data reduction,数据缩减Data set,数据集Data sources,数据来源Data transformation,数据变换Data validity,数据有效性Data-in,数据输入Data-out,数据输出Dead time,停滞期Degree of freedom,自由度Degree of precision,精密度Degree of reliability,可靠性程度Degression,递减Density function,密度函数Density of datapoints,数据点的密度Dependent variable,应变量/依变量/因变量Depth,深度Derivative matrix,导数矩阵Derivative-free methods,无导数方法Design,设计Determinacy,确定性Determinant,行列式Determinant,决定因素Deviation,离差Deviation from average,离均差Diagnostic plot,诊断图Dichotomousvariable,二分变量Differentialequation,微分方程Directstandardization,直接标准化法Discrete variable,离散型变量Discriminant,判断Discriminant analysis,判别分析Discriminant coefficient,判别系数Discriminant function,判别值Dispersion,散布/分散度Disproportional,不成比例的Disproportionate sub-class numbers,不成比例次级组含量Distribution free,分布无关性/免分布Distribution shape,分布形状Distribution-free method,任意分布法Distributive laws,分配律Disturbance,随机扰动项Dose response curve,剂量反应曲线Double blind method,双盲法Doubleblind rial,双盲试验Double exponential distribution,双指数分布Double logarithmic,双对数Downward rank,降秩Dual-space plot,对偶空间图DUD,无导数方法Duncan's new multiple range method,新复极差法/Duncan 新法EEffect, 实验效应Eigen value,特征值Eigen vector,特征向量Ellipse,椭圆Empirical distribution,经验分布Empirical probability,经验概率单位Enumeration data,计数资料Equal sun-class number,相等次级组含量Equally likely,等可能Equal variance,同变性Error,误差/错误Error of estimate,估计误差Error type I,第一类错误Error type II,第二类错误Estimand,被估量Estimated error mean squares,估计误差均方Estimated error sum of squares,估计误差平方和Euclidean distance,欧式距离Event,事件Exceptional data point,异常数据点Expectation plane,期望平面Expectation surface,期望曲面Expected values,期望值Experiment,实验Experimental sampling,试验抽样Experimental unit,试验单位Explanatory variable,说明变量/解释变量Exploratory data analysis,探索性数据分析Explore Summarize,探索-摘要Exponential curve,指数曲线Exponential growth,指数式增长Exsooth,指数平滑方法Extended fit,扩充拟合Extra parameter,附加参数Extra polation,外推法Extreme observation,末端观测值Extremes,极端值/极值FF distribution, F 分布F test, F 检验Factor,因素/因子Factor analysis,因子分析Factor score,因子得分Factorial,阶乘Factorial design,析因试验设计False negative,假阴性False negative error,假阴性错误Family of distributions,分布族Family of estimators,估计量族Fanning,扇面Fatality rate,病死率Field investigation,现场调查Field survey,现场调查Finitepopulation,有限总体Finite-sample, 有限样本Firstderivative,一阶导数First principal component,第一主成分First quartile,第一四分位数Fisher information,费雪信息量Fitted value,拟合值Fitting a curve,曲线拟合Fixed base,定基Fluctuation,随机起伏Forecast,预测Four fold table,四格表Fourth, 四分点Fraction blow,左侧比率Fractional error,相对误差Frequency,频率Frequency polygon,频数多边图Frontier point,界限点Function relationship,泛函关系GGamma distribution,伽玛分布Gauss increment,高斯增量Gaussian distribution,高斯分布/正态分布Gauss-Newton increment,高斯-牛顿增量General census,全面普查GENLOG(Generalized liner models),广义线性模型Geometric mean,几何平均数Gini's mean difference,基尼均差GLM(General liner models),通用线性模型Goodness of fit,拟和优度/配合度Gradientof determinant,行列式的梯度Graeco-Latin square,希腊拉丁方Grand mean,总均值Gross errors,重大错误Gross-error sensitivity,大错敏感度Group averages,分组平均Grouped data,分组资料Guessed mean,假定平均数HHalf-life,半衰期Hampel M-estimators,汉佩尔M 估计量Happenstance,偶然事件Harmonic mean,调和均数Hazard function,风险均数Hazard rate,风险率Heading,标目Heavy-tailed distribution,重尾分布Hessian array,海森立体阵Heterogeneity,不同质Heterogeneity of variance,方差不齐Hierarchical classification,组内分组Hierarchical clustering method,系统聚类法High-leverage point,高杠杆率点HILOGLINEAR,多维列联表的层次对数线性模型Hinge,折叶点Histogram,直方图Historical cohort study,历史性队列研究Holes,空洞HOMALS,多重响应分析Homogeneity of variance,方差齐性Homogeneity test,齐性检验Huber M-estimators,休伯M 估计量Hyperbola,双曲线Hypothesis testing,假设检验Hypothetical universe,假设总体IImpossible event,不可能事件Independence,独立性Independent variable,自变量Index,指标/指数Indirect standardization,间接标准化法Individual,个体Inference band, 推断带Infinite population,无限总体Infinitely great, 无穷大Infinitely small,无穷小Influence curve,影响曲线Information capacity,信息容量Initial condition,初始条件Initial estimate,初始估计值Initial level,最初水平Interaction,交互作用Interaction terms,交互作用项Intercept,截距Interpolation,内插法Inter quartile range,四分位距Interval estimation,区间估计Intervals of equal probability,等概率区间Intrinsic curvature,固有曲率Invariance, 不变性Inverse matrix,逆矩阵Inverse probability,逆概率Inverse sine transformation,反正弦变换Iteration,迭代JJacobian determinant,雅可比行列式Joint distribution function,联合分布函数Joint probability,联合概率Joint probability distribution,联合概率分布KK means method,逐步聚类法Kaplan-Meier,评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier 图Kendall's rank correlation, Kendall 等级相关Kinetic,动力学Kolmogorov-Smirnove test,柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal 及Wallis 检验/多样本的秩和检验/H 检验Kurtosis,峰度LLack of fit,失拟Ladder of powers,幂阶梯Lag,滞后Large sample,大样本Large sample test,大样本检验Latin square,拉丁方Latin square design,拉丁方设计Leakage,泄漏Least favorable configuration,最不利构形Least favorable distribution,最不利分布Least significant difference,最小显著差法Least square method,最小二乘法Least-absolute-residuals estimates,最小绝对残差估计Least-absolute-residuals fit,最小绝对残差拟合Least-absolute-residuals line,最小绝对残差线Legend,图例L-estimator,L 估计量L-estimator of location,位置L 估计量L-estimator of scale,尺度L 估计量Level,水平Life expectance,预期期望寿命Life table,寿命表Life table method,生命表法Light-taile distribution,轻尾分布Likelihood function,似然函数Likelihood ratio,似然比Line graph,线图Linear correlation,直线相关Linear equation,线性方程Linear programming,线性规划Linear regression,直线回归/线性回归Linear trend,线性趋势Loading,载荷Location and scale equi variance,位置尺度同变性Location equi variance,位置同变性Location invariance,位置不变性Location scale family,位置尺度族Log rank test,时序检验Logarithmic curve,对数曲线Logarithmic normal distribution,对数正态分布Logarithmic scale,对数尺度Logarithmic transformation,对数变换Logic check,逻辑检查Logistic distribution,逻辑斯蒂分布Logit transformation, Logit 转换LOGLINEAR,多维列联表通用模型Lognormal distribution,对数正态分布Lost function,损失函数Low correlation,低度相关Lower limit,下限Lowest-attained variance,最小可达方差LSD,最小显著差法的简称Lurking variable,潜在变量MMain effect,主效应Major heading,主辞标目Marginal density function,边缘密度函数Marginal probability,边缘概率Marginal probability distribution,边缘概率分布Matched data,配对资料Matched distribution,匹配过分布Matching of distribution,分布的匹配Matching of transformation,变换的匹配Mathematical expectation,数学期望Mathematical model,数学模型MaximumL-estimator,极大L 估计量Maximumlikelihood method,最大似然法Mean,均数Mean squares between groups,组间均方Mean squares within group,组内均方Means (Compare means),均值-均值比较Median,中位数Median effective dose,半数效量Median lethal dose,半数致死量Median polish,中位数平滑Median test,中位数检验Minimal sufficient statistic,最小充分统计量Minimum distance estimation,最小距离估计Minimum effective dose,最小有效量Minimum lethal dose,最小致死量Minimum variance estimator,最小方差估计量MINITAB,统计软件包Minor heading,宾词标目Missing data,缺失值Model specification,模型的确定Modeling Statistics ,模型统计Models for outliers,离群值模型Modifying the model,模型的修正Modulus of continuity,连续性模Morbidity,发病率Most favorable configuration,最有利构形Multidimensional Scaling (ASCAL),多维尺度/多维标度Multinomial Logistic Regression ,多项逻辑斯蒂回归Multiple comparison,多重比较Multiple correlation ,复相关Multiple covariance,多元协方差Multiple linear regression,多元线性回归Multiple response ,多重选项Multiple solutions,多解Multiplication theorem,乘法定理Multiresponse,多元响应Multi-stage sampling,多阶段抽样Multivariate T distribution,多元T 分布Mutual exclusive,互不相容Mutual independence,互相独立NNatural boundary,自然边界Natural dead,自然死亡Natural zero,自然零Negative correlation,负相关Negative linear correlation,负线性相关Negatively skewed,负偏Newman-Keuls method, q 检验NK method, q 检验No statistical significance,无统计意义Nominal variable,名义变量Nonconstancy of variability,变异的非定常性Nonlinear regression,非线性相关Nonparametric statistics,非参数统计Nonparametric test,非参数检验Normal deviate,正态离差Normal distribution,正态分布Normal equation,正规方程组Normal ranges,正常范围Normal value,正常值Nuisance parameter,多余参数/讨厌参数Null hypothesis,无效假设Numerical variable,数值变量OObjective function,目标函数Observation unit,观察单位Observed value, 观察值One sided test,单侧检验One-way analysis of variance,单因素方差分析One way ANOVA ,单因素方差分析Open sequential trial,开放型序贯设计Optrim, 优切尾Optrim efficiency,优切尾效率Order statistics,顺序统计量Ordered categories,有序分类Ordinal logistic regression ,序数逻辑斯蒂回归Ordinal variable,有序变量Orthogonal basis,正交基Orthogonal design,正交试验设计Orthogonality conditions,正交条件ORTHOPLAN,正交设计Outlier cutoffs,离群值截断点Outliers,极端值OVERALS ,多组变量的非线性正规相关Overshoot,迭代过度PPaired design,配对设计Paired sample,配对样本Pairwise slopes,成对斜率Parabola,抛物线Parallel tests,平行试验Parameter,参数Parametric statistics,参数统计Parametric test,参数检验Partial correlation,偏相关Partial regression,偏回归Partial sorting,偏排序Partials residuals,偏残差Pattern,模式Pearson curves,皮尔逊曲线Peeling,退层Percent bar graph,百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves,百分位曲线Periodicity,周期性Permutation,排列P-estimator,P 估计量Pie graph,饼图Pitman estimator,皮特曼估计量Pivot,枢轴量Planar,平坦Planar assumption,平面的假设PLANCARDS,生成试验的计划卡Point estimation,点估计Poisson distribution,泊松分布Polishing,平滑Polled standard deviation,合并标准差Polled variance,合并方差Polygon,多边图Polynomial,多项式Polynomial curve,多项式曲线Population,总体Population attributable risk,人群归因危险度Positive correlation,正相关Positively skewed,正偏Posterior distribution,后验分布Power of a test,检验效能Precision,精密度Predicted value,预测值Preliminary analysis,预备性分析Principalcomponent analysis,主成分分析Priordistribution,先验分布Prior probability,先验概率Probabilistic model,概率模型probability,概率Probability density,概率密度Product moment,乘积矩/协方差Profile trace,截面迹图Proportion,比/构成比Proportion allocation in stratified random sampling,按比例分层随机抽样Proportionate,成比例Proportionate sub-class numbers,成比例次级组含量Prospective study,前瞻性调查Proximities, 亲近性Pseudo F test,近似F 检验Pseudo model,近似模型Pseudo sigma,伪标准差Purposive sampling,有目的抽样QQR decomposition, QR 分解Quadratic approximation,二次近似Qualitative classification,属性分类Qualitative method,定性方法Quantile-quantile plot,分位数-分位数图/Q-Q 图Quantitative analysis,定量分析Quartile,四分位数Quick Cluster,快速聚类RRadix sort,基数排序Random allocation,随机化分组Random blocks design,随机区组设计Random event,随机事件Randomization,随机化Range,极差/全距Rank correlation,等级相关Rank sum test,秩和检验Rank test,秩检验Ranked data,等级资料Rate,比率Ratio,比例Raw data,原始资料Rawresidual,原始残差Rayleigh's test,雷氏检验Rayleigh's Z,雷氏Z 值Reciprocal,倒数Reciprocal transformation,倒数变换Recording,记录Redescending estimators,回降估计量Reducing dimensions,降维Re-expression,重新表达Reference set,标准组Regionof acceptance,接受域Regression coefficient,回归系数Regression sum of square,回归平方和Rejection point,拒绝点Relative dispersion,相对离散度Relative number,相对数Reliability,可靠性Reparametrization,重新设置参数Replication,重复Report Summaries,报告摘要Residual sum of square,剩余平方和Resistance,耐抗性Resistant line,耐抗线Resistant technique,耐抗技术R-estimator of location,位置R 估计量R-estimator of scale,尺度R 估计量Retrospective study,回顾性调查Ridge trace,岭迹Ridit analysis , Ridit 分析Rotation, 旋转Rounding,舍入Row,行Row effects,行效应Row factor,行因素RXC table, RXC 表SSample,样本Sample regression coefficient,样本回归系数Sample size,样本量Sample standard deviation,样本标准差Sampling error,抽样误差SAS(Statistical analysis system ),SAS 统计软件包Scale,尺度/量表Scatter diagram,散点图Schematic plot,示意图/简图Score test,计分检验Screening,筛检SEASON, 季节分析Second derivative,二阶导数Second principal component,第二主成分SEM (Structural equation modeling),结构化方程模型Semi-logarithmic graph,半对数图Semi-logarithmic paper,半对数格纸Sensitivity curve,敏感度曲线Sequential analysis,贯序分析Sequential data set,顺序数据集Sequential design,贯序设计Sequential method,贯序法Sequential test,贯序检验法Serial tests,系列试验Short-cut method,简捷法Sigmoid curve, S 形曲线Sign function,正负号函数Sign test,符号检验Signed rank,符号秩Significance test,显著性检验Significant figure,有效数字Simple cluster sampling,简单整群抽样Simple correlation,简单相关Simple random sampling,简单随机抽样Simple regression,简单回归simple table,简单表Sine estimator,正弦Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skeweddistribution, 偏斜分布Skewness,偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS 统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwiseregression, 逐步回归Storage,存Strata, 层(复数)Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t 化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival,生存分析Survival rate,生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Test(检验)Test of linearity, 线性检验Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Timeseries, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Twosided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α 错误TypeII error, 二类错误/β 错误UMVU, 方差一致最小无偏估计简称Unbiasedestimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Unweightedleast squares, 未加权最小平方法Upper limit,上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W 检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran 检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方和Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W 估计量W-estimation of location, 位置W 估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z 检验Zero correlation, 零相关Z-transformation, Z 变换。

Asymptotic Theory

Asymptotic Theory

A.1 Convergence in probability (laws of large numbers)
3
Theorem A.4 Markov’s strong law of large numbers. If {zj } is sequence of independent random variables with E [zj ] = µj < 1+ E |zj µj | and if for some > 0, < then z n µn converges almost j 1+ n n surely to 0, where z n = n1 zj and µn = n1 µj .
nLeabharlann A frequently employed special case is convergence in quadratic mean. Theorem A.1 Convergence in quadratic mean (or mean square). If xn has mean µn and variance 2 n such that ordinary limits of µn and
n j =1
Almost sure convergence implies convergence in probability (but not necessarily the converse).
A.1.2 Applications of convergence
Definition A.3 Consistent estimator. An estimator ˆ of parameter is a consistent estimator i p lim ˆ = .

行政许可法英文版本

行政许可法英文版本

行政许可法英文版本Administrative Licensing LawChapter I General ProvisionsArticle 1 This Law is enacted in accordance with the Constitution and in the light of the specific circumstances in China to regulate the administrative licensing activities of administrative organs, protect the lawful rights and interests of citizens, legal persons and other organizations, promote the reform of the administrative system and maintain the order of administrative management.Article 2 Administrative licensing, as used in this Law, refers to the activities whereby administrative organs examine and approve or certify the qualifications of subjects or events that are subject to examination or approval under the law in accordance with legal procedures.Article 3 When conducting administrative licensing activities, administrative organs shall adhere to the principles of lawfulness, openness, impartiality, efficiency and convenience, and respect and protect the lawful rights and interests of citizens, legal persons and other organizations.Article 4 Administrative organs shall establish and improve the administrative licensing management system, formulate andpublish the administrative licensing catalogue, simplify, standardize and supervise the administrative licensing procedures, increase transparency of administrative licensing activities, and ensure the fairness, impartiality, and efficiency of administrative licensing.Article 5 Where any law or administrative regulation prescribes that the interests of the State or the public interest shall be protected by means of administrative licensing, or that a specific matter shall be subject to administrative licensing, the relevant administrative organ shall, in accordance with legal procedures, conduct administrative licensing activities in accordance with the provisions of this Law.Article 6 Where any law, administrative regulation, or departmental rule prescribes that administrative licensing matters are subject to division of duties between administrative organs or shared by several administrative organs, the administrative organ that is responsible for the licensing matter shall coordinate and cooperate with other administrative organs or seek their opinions, and the relevant administrative organ shall, in accordance with the law and by the principle of division of duties or sharing of responsibilities, conduct administrative licensing activities in accordance with the provisions of this Law, and the responsibilities of other administrative organs shall not be replaced.Article 7 An applicant's refusal to accept administrative licensing decisions made in accordance with legal procedures shall not affect the effectiveness of the administrative licensing decisions. A party who refuses to accept an administrative licensing decision may apply for administrative reconsideration or bring an administrative lawsuit in accordance with the law.Chapter II Catalogue and Standardization of Administrative LicensingArticle 8 The State shall establish and publish an administrative licensing catalogue, and regularly update and modify it as necessary.Article 9 The administrative licensing catalogue shall clearly specify the scope, contents, conditions and procedures for examination and approval of administrative licensing matters, and the basis for responsibility, the known time limit for processing, and the charging basis and standard of fees.Article 10 Where any law, administrative regulation or departmental rule prescribes that an administrative license is required for the establishment or activities of a citizen, a legal person, or other organization, the relevant administrative organ shall specify the matters, scope and procedures for the administrative license in accordance with the provisions of these regulations.Article 11 When promulgating rules or normative documents related to administrative licensing, the administrative organ shall specify the matters, scope, procedures for examination and approval, and basis for responsibility under the administrative license in accordance with the provisions of these regulations, and shall not extend the scope of administrative licensing.Chapter III Examination and Approval Procedures for Administrative LicensingArticle 12 An applicant shall submit an application for administrative licensing matters to the relevant administrative organ, and the administrative organ shall accept the application.Article 13 The administrative organ shall, within the time limit specified in the administrative licensing catalogue, make a decision to approve the administrative license or provide a written explanation of the reasons for not approving. If the administrative licensing matters involve other administrative organs or other organizations, opinions shall be sought first before making a decision.Article 14 The administrative organ shall, when examining and approving administrative licensing matters, verify the authenticity, legality, necessity, and feasibility of the application materials, and may, if necessary, require the applicant to supplement or correct the application materials.Article 15 The administrative organ shall conduct on-site inspections as needed for administrative licensing matters. When conducting on-site inspections, the administrative organ shall produce legal documents and verify with the subject of the inspection. The subjects of the inspection shall not refuse or obstruct the inspection. The administrative organ shall keep a written record of the results of the inspection.Article 16 The administrative organ shall make a decision on administrative licensing matters based on the examination results, and shall notify the applicant in writing of the decision within the time limit specified in the administrative licensing catalogue.Article 17 If an applicant fails to obtain the administrative license due to the fault of the administrative organ, the applicant has the right to request that the administrative organ compensate for any losses.Chapter IV Supervision and Management of Administrative LicensingArticle 18 Administrative licensing matters shall be subject to periodic evaluation by the relevant administrative organs. The administrative organs shall improve the administrative licensing procedures based on the results of the evaluation, and shall publish the results of the evaluation in a timely manner. The administrative licensing process shall be regularly reviewed and adjusted.Article 19 The public has the right to supervise and report on administrative licensing activities. Administrative organs shall establish and improve complaint systems and shall not retaliate against the reporter.Article 20 The administrative organ shall establish a management system for administrative licensing and shall strictly enforce it. The administrative organ shall provide corresponding training and guidance for personnel involved in administrative licensing activities, make public the criteria for evaluating the performance of personnel, and implement a system of rewards and punishments.Article 21 Administrative fees and charges collected by administrative organs shall be paid to the State Treasury in accordance with the law. Administrative organs shall not collect any fees in excess of the statutory fees and shall not solicit or receive any illegal fees.Chapter V Legal LiabilityArticle 22 An administrative organ that violates the provisions of this law by exceeding its authority, neglecting its duties, or making illegal decisions, shall be subject to administrative sanctions in accordance with the law, and shall compensate the losses caused to citizens, legal persons, or other organizations.Article 23 The administrative staff who violates the provisions of this law by taking advantage of their position to seek benefits, soliciting or accepting bribes, abusing their power to conduct illegal activities, or neglecting their duties, shall be subject to disciplinary action by the Party or the nation in accordance with the law, and shall be held criminally responsible if their conduct constitutes a crime.Chapter VI Supplementary ProvisionsArticle 24 This Law shall come into force on July 1, 2004. The Administrative Licensing Measures for Jiangsu Province promulgated by the Jiangsu Provincial People's Government on October 23, 1986, shall be repealed simultaneously.。

统计学专业名词(中英对照)

统计学专业名词(中英对照)

统计学专业名词·中英对照我大学毕业已经多年,这些年来,越发感到外刊的重要性。

读懂外刊要有不错的英语功底,同时,还需要掌握一定的专业词汇。

掌握足够的专业词汇,在国内外期刊的阅读和写作中会游刃有余。

在此小结,按首字母顺序排列。

这些词汇的来源,一是专业书籍,二是网上查找,再一个是比较重要的期刊。

当然,这些仅是常用专业词汇的一部分,并且由于个人精力、文献查阅的限制,难免有不足和错误之处,希望读者批评指出。

Aabscissa 横坐标absence rate 缺勤率Absolute deviation 绝对离差Absolute number 绝对数absolute value 绝对值Absolute residuals 绝对残差accident error 偶然误差Acceleration array 加速度立体阵Acceleration in an arbitrary direction 任意方向上的加速度Acceleration normal 法向加速度Acceleration space dimension 加速度空间的维数Acceleration tangential 切向加速度Acceleration vector 加速度向量Acceptable hypothesis 可接受假设Accumulation 累积Accumulated frequency 累积频数Accuracy 准确度Actual frequency 实际频数Adaptive estimator 自适应估计量Addition 相加Addition theorem 加法定理Additive Noise 加性噪声Additivity 可加性Adjusted rate 调整率Adjusted value 校正值Admissible error 容许误差Aggregation 聚集性Alpha factori ng α因子法Alternative hypothesis 备择假设Among groups 组间Amounts 总量Analysis of correlation 相关分析Analysis of covariance 协方差分析Analysis of data 分析资料Analysis Of Effects 效应分析Analysis Of Variance 方差分析Analysis of regression 回归分析Analysis of time series 时间序列分析Analysis of variance 方差分析Angular transformation 角转换ANOVA (analysis of variance)方差分析ANOVA Models 方差分析模型ANOVA table and eta 分组计算方差分析Arcing 弧/弧旋Arcsine transformation 反正弦变换Area 区域图Area under the curve 曲线面积AREG 评估从一个时间点到下一个时间点回归相关时的误差ARIMA 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper 算术格纸Arithmetic mean 算术平均数Arithmetic weighted mean 加权算术均数Arrhenius relation 艾恩尼斯关系Assessing fit 拟合的评估Associative laws 结合律Assumed mean 假定均数Asymmetric distribution 非对称分布Asymmetry coefficient 偏度系数Asymptotic bias 渐近偏倚Asymptotic efficiency 渐近效率Asymptotic variance 渐近方差Attributable risk 归因危险度Attribute data 属性资料Attribution 属性Autocorrelation 自相关Autocorrelation of residuals 残差的自相关Average 平均数Average confidence interval length 平均置信区间长度average deviation 平均差Average growth rate 平均增长率BBar chart/graph 条形图Base period 基期Bayes' theorem Bayes 定理Bell-shaped curve 钟形曲线Bernoulli distribution 伯努力分布Best-trim estimator 最好切尾估计量Bias 偏性Biometrics 生物统计学Binary logistic regression 二元逻辑斯蒂回归Binomial distribution 二项分布Bisquare 双平方Bivariate Correlate 二变量相关Bivariate normal distribution 双变量正态分布Bivariate normal population 双变量正态总体Biweight interval 双权区间Biweight M-estimator 双权M 估计量Block 区组/配伍组BMDP(Biomedical computer programs) BMDP 统计软件包Box plot 箱线图/箱尾图Breakdown bound 崩溃界/崩溃点CCanonical correlation 典型相关Caption 纵标目Cartogram 统计图Case fatality rate 病死率Case-control study 病例对照研究Categorical variable 分类变量Catenary 悬链线Cauchy distribution 柯西分布Cause-and-effect relationship 因果关系Cell 单元Censoring 终检census 普查Center of symmetry 对称中心Centering and scaling 中心化和定标Central tendency 集中趋势Central value 中心值CHAID -χ2 Automatic Interaction Detector 卡方自动交互检测Chance 机遇Chance error 随机误差Chance variable 随机变量Characteristic equation 特征方程Characteristic root 特征根Characteristic vector 特征向量Chebshev criterion of fit 拟合的切比雪夫准则Chernoff faces 切尔诺夫脸谱图chi-sguare(X2) test 卡方检验卡方检验/χ2 检验Choleskey decomposition 乔洛斯基分解Circle chart 圆图Class interval 组距Classification 分组、分类Class mid-value 组中值Class upper limit 组上限Classified variable 分类变量Cluster analysis 聚类分析Cluster sampling 整群抽样Code 代码Coded data 编码数据Coding 编码Coefficient of contingency 列联系数Coefficient of correlation 相关系数Coefficient of determination 决定系数Coefficient of multiple correlation 多重相关系数Coefficient of partial correlation 偏相关系数Coefficient of production-moment correlation 积差相关系数Coefficient of rank correlation 等级相关系数Coefficient of regression 回归系数Coefficient of skewness 偏度系数Coefficient of variation 变异系数Cohort study 队列研究Collection of data 资料收集Collinearity 共线性Column 列Column effect 列效应Column factor 列因素Combination pool 合并Combinative table 组合表Combined standard deviation 合并标准差Combined variance 合并方差Common factor 共性因子Common regression coefficient 公共回归系数Common value 共同值Common variance 公共方差Common variation 公共变异Communality variance 共性方差Comparability 可比性Comparison of bathes 批比较Comparison value 比较值Compartment model 分部模型Compassion 伸缩Complement of an event 补事件Complete association 完全正相关Complete dissociation 完全不相关Complete statistics 完备统计量Complete survey 全面调查Completely randomized design 完全随机化设计Composite event 联合事件Composite events 复合事件Concavity 凹性Conditional expectation 条件期望Conditional likelihood 条件似然Conditional probability 条件概率Conditionally linear 依条件线性Confidence interval 置信区间Confidence level 可信水平,置信水平Confidence limit 置信限Confidence lower limit 置信下限Confidence upper limit 置信上限Confirmatory Factor Analysis 验证性因子分析Confirmatory research 证实性实验研究Confounding factor 混杂因素Conjoint 联合分析Consistency 相合性Consistency check 一致性检验Consistent asymptotically normal estimate 相合渐近正态估计Consistent estimate 相合估计Constituent ratio 构成比,结构相对数Constrained nonlinear regression 受约束非线性回归Constraint 约束Contaminated distribution 污染分布Contaminated Gausssian 污染高斯分布Contaminated normal distribution 污染正态分布Contamination 污染Contamination model 污染模型Continuity 连续性Contingency table 列联表Contour 边界线Contribution rate 贡献率Control 对照质量控制图Control group 对照组Controlled experiments 对照实验Conventional depth 常规深度Convolution 卷积Coordinate 坐标Corrected factor 校正因子Corrected mean 校正均值Correction coefficient 校正系数Correction for continuity 连续性校正Correction for grouping 归组校正Correction number 校正数Correction value 校正值Correctness 正确性Correlation 相关,联系Correlation analysis 相关分析Correlation coefficient 相关系数Correlation 相关性Correlation index 相关指数Correspondence 对应Counting 计数Counts 计数/频数Covariance 协方差Covariant 共变Cox Regression Cox 回归Criteria for fitting 拟合准则Criteria of least squares 最小二乘准则Critical ratio 临界比Critical region 拒绝域Critical value 临界值Cross-over design 交叉设计Cross-section analysis 横断面分析Cross-section survey 横断面调查Crosstabs 交叉表Crosstabs 列联表分析Cross-tabulation table 复合表Cube root 立方根Cumulative distribution function 分布函数Cumulative frequency 累积频率Cumulative probability 累计概率Curvature 曲率/弯曲Curvature 曲率Curve Estimation 曲线拟合Curve fit 曲线拟和Curve fitting 曲线拟合Curvilinear regression 曲线回归Curvilinear relation 曲线关系Cut-and-try method 尝试法Cycle 周期Cyclist 周期性DD test D 检验data 资料Data acquisition 资料收集Data bank 数据库Data capacity 数据容量Data deficiencies 数据缺乏Data handling 数据处理Data manipulation 数据处理Data processing 数据处理Data reduction 数据缩减Data set 数据集Data sources 数据来源Data transformation 数据变换Data validity 数据有效性Data-in 数据输入Data-out 数据输出Dead time 停滞期Degree of freedom 自由度degree of confidence 可信度,置信度degree of dispersion 离散程度Degree of precision 精密度Degree of reliability 可靠性程度degree of variation 变异度Degression 递减Density function 密度函数Density of data points 数据点的密度Dependent variableDepth 深度Derivative matrix 导数矩阵Derivative-free methods 无导数方法Design 设计design of experiment 实验设计Determinacy 确定性Determinant 行列式Determinant 决定因素Deviation 离差Deviation from average 离均差diagnose accordance rate 诊断符合率Diagnostic plot 诊断图Dichotomous variable 二分变量Differential equation 微分方程Direct standardization 直接标准化法Direct Oblimin 斜交旋转Discrete variable 离散型变量DISCRIMINANT 判断Discriminant analysis 判别分析Discriminant coefficient 判别系数Discriminant function 判别值Dispersion 散布/分散度Disproportional 不成比例的Disproportionate sub-class numbers 不成比例次级组含量Distribution free 分布无关性/免分布Distribution shape 分布形状Distribution-free method 任意分布法Distributive laws 分配律Disturbance 随机扰动项Dose response curve 剂量反应曲线Double blind method 双盲法Double blind trial 双盲试验Double exponential distribution 双指数分布Double logarithmic 双对数Downward rank 降秩Dual-space plot 对偶空间图DUD 无导数方法Duncan's new multiple range method 新复极差法/Duncan 新法EError Bar 均值相关区间图Effect 实验效应Effective rate 有效率Eigenvalue 特征值Eigenvector 特征向量Ellipse 椭圆Empirical distribution 经验分布Empirical probability 经验概率单位Enumeration data 计数资料Equal sun-class number 相等次级组含量Equally likely 等可能Equation of linear regression 线性回归方程Equivariance 同变性Error 误差/错误Error of estimate 估计误差Error of replication 重复误差Error type I 第一类错误Error type II 第二类错误Estimand 被估量Estimated error mean squares 估计误差均方Estimated error sum of squares 估计误差平方和Euclidean distance 欧式距离Event 事件Exceptional data point 异常数据点Expectation plane 期望平面Expectation surface 期望曲面Expected values 期望值Experiment 实验Experiment design 实验设计Experiment error 实验误差Experimental group 实验组Experimental sampling 试验抽样Experimental unit 试验单位Explained variance (已说明方差)Explanatory variable 说明变量Exploratory data analysis 探索性数据分析Explore Summarize 探索-摘要Exponential curve 指数曲线Exponential growth 指数式增长EXSMOOTH 指数平滑方法Extended fit 扩充拟合Extra parameter 附加参数Extrapolation 外推法Extreme observation 末端观测值Extremes 极端值/极值FF distribution F 分布F test F 检验Factor 因素/因子Factor analysis 因子分析Factor Analysis 因子分析Factor score 因子得分Factorial 阶乘Factorial design 析因试验设计False negative 假阴性False negative error 假阴性错误Family of distributions 分布族Family of estimators 估计量族Fanning 扇面Fatality rate 病死率Field investigation 现场调查Field survey 现场调查Finite population 有限总体Finite-sample 有限样本First derivative 一阶导数First principal component 第一主成分First quartile 第一四分位数Fisher information 费雪信息量Fitted value 拟合值Fitting a curve 曲线拟合Fixed base 定基Fluctuation 随机起伏Forecast 预测Four fold table 四格表Fourth 四分点Fraction blow 左侧比率Fractional error 相对误差Frequency 频率Freguency distribution 频数分布Frequency polygon 频数多边图Frontier point 界限点Function relationship 泛函关系GGamma distribution 伽玛分布Gauss increment 高斯增量Gaussian distribution 高斯分布/正态分布Gauss-Newton increment 高斯-牛顿增量General census 全面普查Generalized least squares 综合最小平方法GENLOG (Generalized liner models) 广义线性模型Geometric mean 几何平均数Gini's mean difference 基尼均差GLM (General liner models) 通用线性模型Goodness of fit 拟和优度/配合度Gradient of determinant 行列式的梯度Graeco-Latin square 希腊拉丁方Grand mean 总均值Gross errors 重大错误Gross-error sensitivity 大错敏感度Group averages 分组平均Grouped data 分组资料Guessed mean 假定平均数HHalf-life 半衰期Hampel M-estimators 汉佩尔M 估计量Happenstance 偶然事件Harmonic mean 调和均数Hazard function 风险均数Hazard rate 风险率Heading 标目Heavy-tailed distribution 重尾分布Hessian array 海森立体阵Heterogeneity 不同质Heterogeneity of variance 方差不齐Hierarchical classification 组内分组Hierarchical clustering method 系统聚类法High-leverage point 高杠杆率点High-Low 低区域图Higher Order Interaction Effects,高阶交互作用HILOGLINEAR 多维列联表的层次对数线性模型Hinge 折叶点Histogram 直方图Historical cohort study 历史性队列研究Holes 空洞HOMALS 多重响应分析Homogeneity of variance 方差齐性Homogeneity test 齐性检验Huber M-estimators 休伯M 估计量Hyperbola 双曲线Hypothesis testing 假设检验Hypothetical universe 假设总体IImage factoring 多元回归法Impossible event 不可能事件Independence 独立性Independent variable 自变量Index 指标/指数Indirect standardization 间接标准化法Individual 个体Inference band 推断带Infinite population 无限总体Infinitely great 无穷大Infinitely small 无穷小Influence curve 影响曲线Information capacity 信息容量Initial condition 初始条件Initial estimate 初始估计值Initial level 最初水平Interaction 交互作用Interaction terms 交互作用项Intercept 截距Interpolation 内插法Interquartile range 四分位距Interval estimation 区间估计Intervals of equal probability 等概率区间Intrinsic curvature 固有曲率Invariance 不变性Inverse matrix 逆矩阵Inverse probability 逆概率Inverse sine transformation 反正弦变换Iteration 迭代JJacobian determinant 雅可比行列式Joint distribution function 分布函数Joint probability 联合概率Joint probability distribution 联合概率分布KK-Means Cluster 逐步聚类分析K means method 逐步聚类法Kaplan-Meier 评估事件的时间长度Kaplan-Merier chart Kaplan-Merier 图Kendall's rank correlation Kendall 等级相关Kinetic 动力学Kolmogorov-Smirnove test 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test Kruskal 及Wallis 检验/多样本的秩和检验/H 检验Kurtosis 峰度LLack of fit 失拟Ladder of powers 幂阶梯Lag 滞后Large sample 大样本Large sample test 大样本检验Latin square 拉丁方Latin square design 拉丁方设计Leakage 泄漏Least favorable configuration 最不利构形Least favorable distribution 最不利分布Least significant difference 最小显著差法Least square method 最小二乘法Least Squared Criterion,最小二乘方准则Least-absolute-residuals estimates 最小绝对残差估计Least-absolute-residuals fit 最小绝对残差拟合Least-absolute-residuals line 最小绝对残差线Legend 图例L-estimator L 估计量L-estimator of location 位置L 估计量L-estimator of scale 尺度L 估计量Level 水平Leveage Correction,杠杆率校正Life expectance 预期期望寿命Life table 寿命表Life table method 生命表法Light-tailed distribution 轻尾分布Likelihood function 似然函数Likelihood ratio 似然比line graph 线图Linear equation 线性方程Linear programming 线性规划Linear regression 直线回归Linear Regression 线性回归Linear trend 线性趋势Loading 载荷Location and scale equivariance 位置尺度同变性Location equivariance 位置同变性Location invariance 位置不变性Location scale family 位置尺度族Log rank test 时序检验Logarithmic curve 对数曲线Logarithmic normal distribution 对数正态分布Logarithmic scale 对数尺度Logarithmic transformation 对数变换Logic check 逻辑检查Logistic distribution 逻辑斯特分布Logit transformation Logit 转换LOGLINEAR 多维列联表通用模型Lognormal distribution 对数正态分布Lost function 损失函数Lower limit 下限Lowest-attained variance 最小可达方差LSD 最小显著差法的简称Lurking variable 潜在变量MMain effect 主效应Major heading 主辞标目Marginal density function 边缘密度函数Marginal probability 边缘概率Marginal probability distribution 边缘概率分布Matched data 配对资料Matched distribution 匹配过分布Matching of distribution 分布的匹配Matching of transformation 变换的匹配Mathematical expectation 数学期望Mathematical model 数学模型Maximum L-estimator 极大极小L 估计量Maximum likelihood method 最大似然法Mean 均数Mean squares between groups 组间均方Mean squares within group 组内均方Means (Compare means) 均值-均值比较Median 中位数Median effective dose 半数效量Median lethal dose 半数致死量Median polish 中位数平滑Median test 中位数检验Minimal sufficient statistic 最小充分统计量Minimum distance estimation 最小距离估计Minimum effective dose 最小有效量Minimum lethal dose 最小致死量Minimum variance estimator 最小方差估计量MINITAB 统计软件包Minor heading 宾词标目Missing data 缺失值Model specification 模型的确定Modeling Statistics 模型统计Models for outliers 离群值模型Modifying the model 模型的修正Modulus of continuity 连续性模Morbidity 发病率Most favorable configuration 最有利构形MSC(多元散射校正)Multidimensional Scaling (ASCAL) 多维尺度/多维标度Multinomial Logistic Regression 多项逻辑斯蒂回归Multiple comparison 多重比较Multiple correlation 复相关Multiple covariance 多元协方差Multiple linear regression 多元线性回归Multiple response 多重选项Multiple solutions 多解Multiplication theorem 乘法定理Multiresponse 多元响应Multi-stage sampling 多阶段抽样Multivariate T distribution 多元T 分布Mutual exclusive 互不相容Mutual independence 互相独立NNatural boundary 自然边界Natural dead 自然死亡Natural zero 自然零Negative correlation 负相关Negative linear correlation 负线性相关Negatively skewed 负偏Newman-Keuls method q 检验NK method q 检验No statistical significance 无统计意义Nominal variable 名义变量Nonconstancy of variability 变异的非定常性Nonlinear regression 非线性相关Nonparametric statistics 非参数统计Nonparametric test 非参数检验Nonparametric tests 非参数检验Normal deviate 正态离差Normal distribution 正态分布Normal equation 正规方程组Normal P-P 正态概率分布图Normal Q-Q 正态概率单位分布图Normal ranges 正常范围Normal value 正常值Normalization 归一化Nuisance parameter 多余参数/讨厌参数Null hypothesis 无效假设Numerical variable 数值变量OObjective function 目标函数Observation unit 观察单位Observed value 观察值One sided test 单侧检验One-way analysis of variance 单因素方差分析Oneway ANOVA 单因素方差分析Open sequential trial 开放型序贯设计Optrim 优切尾Optrim efficiency 优切尾效率Order statistics 顺序统计量Ordered categories 有序分类Ordinal logistic regression 序数逻辑斯蒂回归Ordinal variable 有序变量Orthogonal basis 正交基Orthogonal design 正交试验设计Orthogonality conditions 正交条件ORTHOPLAN 正交设计Outlier cutoffs 离群值截断点Outliers 极端值OVERALS 多组变量的非线性正规相关Overshoot 迭代过度PPaired design 配对设计Paired sample 配对样本Pairwise slopes 成对斜率Parabola 抛物线Parallel tests 平行试验Parameter 参数Parametric statistics 参数统计Parametric test 参数检验Pareto 直条构成线图(佩尔托图)Partial correlation 偏相关Partial regression 偏回归Partial sorting 偏排序Partials residuals 偏残差Pattern 模式PCA(主成分分析)Pearson curves 皮尔逊曲线Peeling 退层Percent bar graph 百分条形图Percentage 百分比Percentile 百分位数Percentile curves 百分位曲线Periodicity 周期性Permutation 排列P-estimator P 估计量Pie graph 构成图饼图Pitman estimator 皮特曼估计量Pivot 枢轴量Planar 平坦Planar assumption 平面的假设PLANCARDS 生成试验的计划卡PLS(偏最小二乘法)Point estimation 点估计Poisson distribution 泊松分布Polishing 平滑Polled standard deviation 合并标准差Polled variance 合并方差Polygon 多边图Polynomial 多项式Polynomial curve 多项式曲线Population 总体Population attributable risk 人群归因危险度Positive correlation 正相关Positively skewed 正偏Posterior distribution 后验分布Power of a test 检验效能Precision 精密度Predicted value 预测值Preliminary analysis 预备性分析Principal axis factoring 主轴因子法Principal component analysis 主成分分析Prior distribution 先验分布Prior probability 先验概率Probabilistic model 概率模型probability 概率Probability density 概率密度Product moment 乘积矩/协方差Profile trace 截面迹图Proportion 比/构成比Proportion allocation in stratified random sampling 按比例分层随机抽样Proportionate 成比例Proportionate sub-class numbers 成比例次级组含量Prospective study 前瞻性调查Proximities 亲近性Pseudo F test 近似F 检验Pseudo model 近似模型Pseudosigma 伪标准差Purposive sampling 有目的抽样QQR decomposition QR 分解Quadratic approximation 二次近似Qualitative classification 属性分类Qualitative method 定性方法Quantile-quantile plot 分位数-分位数图/Q-Q 图Quantitative analysis 定量分析Quartile 四分位数Quick Cluster 快速聚类RRadix sort 基数排序Random allocation 随机化分组Random blocks design 随机区组设计Random event 随机事件Randomization 随机化Range 极差/全距Rank correlation 等级相关Rank sum test 秩和检验Rank test 秩检验Ranked data 等级资料Rate 比率Ratio 比例Raw data 原始资料Raw residual 原始残差Rayleigh's test 雷氏检验Rayleigh's Z 雷氏Z 值Reciprocal 倒数Reciprocal transformation 倒数变换Recording 记录Redescending estimators 回降估计量Reducing dimensions 降维Re-expression 重新表达Reference set 标准组Region of acceptance 接受域Regression coefficient 回归系数Regression sum of square 回归平方和Rejection point 拒绝点Relative dispersion 相对离散度Relative number 相对数Reliability 可靠性Reparametrization 重新设置参数Replication 重复Report Summaries 报告摘要Residual sum of square 剩余平方和residual variance (剩余方差)Resistance 耐抗性Resistant line 耐抗线Resistant technique 耐抗技术R-estimator of location 位置R 估计量R-estimator of scale 尺度R 估计量Retrospective study 回顾性调查Ridge trace 岭迹Ridit analysis Ridit 分析Rotation 旋转Rounding 舍入Row 行Row effects 行效应Row factor 行因素RXC table RXC 表SSample 样本Sample regression coefficient 样本回归系数Sample size 样本量Sample standard deviation 样本标准差Sampling error 抽样误差SAS(Statistical analysis system ) SAS 统计软件包Scale 尺度/量表Scatter diagram 散点图Schematic plot 示意图/简图Score test 计分检验Screening 筛检SEASON 季节分析Second derivative 二阶导数Second principal component 第二主成分SEM (Structural equation modeling) 结构化方程模型Semi-logarithmic graph 半对数图Semi-logarithmic paper 半对数格纸Sensitivity curve 敏感度曲线Sequential analysis 贯序分析Sequence 普通序列图Sequential data set 顺序数据集Sequential design 贯序设计Sequential method 贯序法Sequential test 贯序检验法Serial tests 系列试验Short-cut method 简捷法Sigmoid curve S 形曲线Sign function 正负号函数Sign test 符号检验Signed rank 符号秩Significant Level 显著水平Significance test 显著性检验Significant figure 有效数字Simple cluster sampling 简单整群抽样Simple correlation 简单相关Simple random sampling 简单随机抽样Simple regression 简单回归simple table 简单表Sine estimator 正弦估计量Single-valued estimate 单值估计Singular matrix 奇异矩阵Skewed distribution 偏斜分布Skewness 偏度Slash distribution 斜线分布Slope 斜率Smirnov test 斯米尔诺夫检验Source of variation 变异来源Spearman rank correlation 斯皮尔曼等级相关Specific factor 特殊因子Specific factor variance 特殊因子方差Spectra 频谱Spherical distribution 球型正态分布Spread 展布SPSS(Statistical package for the social science) SPSS 统计软件包Spurious correlation 假性相关Square root transformation 平方根变换Stabilizing variance 稳定方差Standard deviation 标准差Standard error 标准误Standard error of difference 差别的标准误Standard error of estimate 标准估计误差Standard error of rate 率的标准误Standard normal distribution 标准正态分布Standardization 标准化Starting value 起始值Statistic 统计量Statistical control 统计控制Statistical graph 统计图Statistical inference 统计推断Statistical table 统计表Steepest descent 最速下降法Stem and leaf display 茎叶图Step factor 步长因子Stepwise regression 逐步回归Storage 存Strata 层(复数)Stratified sampling 分层抽样Stratified sampling 分层抽样Strength 强度Stringency 严密性Structural relationship 结构关系Studentized residual 学生化残差/t 化残差Sub-class numbers 次级组含量Subdividing 分割Sufficient statistic 充分统计量Sum of products 积和Sum of squares 离差平方和Sum of squares about regression 回归平方和Sum of squares between groups 组间平方和Sum of squares of partial regression 偏回归平方和Sure event 必然事件Survey 调查Survival 生存分析Survival rate 生存率Suspended root gram 悬吊根图Symmetry 对称Systematic error 系统误差Systematic sampling 系统抽样TTags 标签Tail area 尾部面积Tail length 尾长Tail weight 尾重Tangent line 切线Target distribution 目标分布Taylor series 泰勒级数Test(检验)Test of linearity 线性检验Tendency of dispersion 离散趋势Testing of hypotheses 假设检验Theoretical frequency 理论频数Time series 时间序列Tolerance interval 容忍区间Tolerance lower limit 容忍下限Tolerance upper limit 容忍上限Torsion 扰率Total sum of square 总平方和Total variation 总变异Transformation 转换Treatment 处理Trend 趋势Trend of percentage 百分比趋势Trial 试验Trial and error method 试错法Tuning constant 细调常数Two sided test 双向检验Two-stage least squares 二阶最小平方Two-stage sampling 二阶段抽样Two-tailed test 双侧检验Two-way analysis of variance 双因素方差分析Two-way table 双向表Type I error 一类错误/α错误Type II error 二类错误/β错误UUMVU 方差一致最小无偏估计简称Unbiased estimate 无偏估计Unconstrained nonlinear regression 无约束非线性回归Unequal subclass number 不等次级组含量Ungrouped data 不分组资料Uniform coordinate 均匀坐标Uniform distribution 均匀分布Uniformly minimum variance unbiased estimate 方差一致最小无偏估计Unit 单元Unordered categories 无序分类Unweighted least squares 未加权最小平方法Upper limit 上限Upward rank 升秩VVague concept 模糊概念Validity 有效性V ARCOMP (Variance component estimation) 方差元素估计Variability 变异性Variable 变量Variance 方差Variation 变异Varimax orthogonal rotation 方差最大正交旋转V olume of distribution 容积WW test W 检验Weibull distribution 威布尔分布Weight 权数Weighted Chi-square test 加权卡方检验/Cochran 检验Weighted linear regression method 加权直线回归Weighted mean 加权平均数Weighted mean square 加权平均方差Weighted sum of square 加权平方和Weighting coefficient 权重系数Weighting method 加权法W-estimation W 估计量W-estimation of location 位置W 估计量Width 宽度Wilcoxon paired test 威斯康星配对法/配对符号秩和检验Wild point 野点/狂点Wild value 野值/狂值Winsorized mean 缩尾均值Withdraw 失访X此组的词汇还没找到YYouden's index 尤登指数ZZ test Z 检验Zero correlation 零相关Z-transformation Z 变换。

统计学常用英语词汇

统计学常用英语词汇

统计学常用英语词汇Absolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additive Noise, 加性噪声Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alpha factoring,α因子法Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis Of Effects, 效应分析Analysis Of Variance, 方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOVA (analysis of variance), 方差分析ANOVA Models, 方差分析模型ANOVA table and eta, 分组计算方差分析Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area 区域图Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper, 算术格纸Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal ranges, 正常范围Normal value, 正常值Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Partial correlation, 偏相关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Profile trace, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling, 按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 接受域Regression coefficient, 回归系数Regression sum of square, 回归平方和Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方和Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system ), SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significance test, 显著性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单相关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层(复数)Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Two sided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α错误Type II error, 二类错误/β错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Upper limit, 上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方和Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W估计量W-estimation of location, 位置W估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z检验Zero correlation, 零相关Z-transformation, Z变换。

品质英语

品质英语

品质英语A-DAbsolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOVA (analysis of variance), 方差分析ANOVA Models, 方差分析模型Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法E-LEffect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量。

计量经济学中英文词汇对照

计量经济学中英文词汇对照

Common variance Common variation Communality variance Comparability Comparison of bathes Comparison value Compartment model Compassion Complement of an event Complete association Complete dissociation Complete statistics Completely randomized design Composite event Composite events Concavity Conditional expectation Conditional likelihood Conditional probability Conditionally linear Confidence interval Confidence limit Confidence lower limit Confidence upper limit Confirmatory Factor Analysis Confirmatory research Confounding factor Conjoint Consistency Consistency check Consistent asymptotically normal estimate Consistent estimate Constrained nonlinear regression Constraint Contaminated distribution Contaminated Gausssian Contaminated normal distribution Contamination Contamination model Contingency table Contour Contribution rate Control
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a rX iv:mat h /51269v2[mat h.CO]14J u l25ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS OMER GIM ´ENEZ AND MARC NOY Abstract.We present a complete analytic solution to the problem of count-ing planar graphs.We prove an estimate g n ∼g ·n −7/2γn n !for the number g n of labelled planar graphs on n vertices,where γand g are explicit computable constants.We show that the number of edges in random planar graphs is asymptotically normal with linear mean and variance and,as a consequence,the number of edges is sharply concentrated around its expected value.More-over we prove an estimate g (q )·n −4γ(q )n n !for the number of planar graphs with n vertices and ⌊qn ⌋edges,where γ(q )is an analytic function of q .We also show that the number of connected components in a random planar graph is distributed asymptotically as a shifted Poisson law 1+P (ν),where νis an ex-plicit constant.Additional Gaussian and Poisson limit laws for random planar graphs are derived.The proofs are based on singularity analysis of generating functions and on perturbation of singularities.1.Introduction and statement of results In this paper we obtain a precise asymptotic estimate for the number of labelled planar graphs on n vertices,and we establish limit laws for several parameters in random labelled planar graphs.In particular,we show that the number of edges in random planar graphs is asymptotically normal,and that the number of connected components in a random planar graph is distributed asymptotically as a shifted Poisson law.Additional Gaussian and Poisson limit laws for random planar graphs are derived.From now on,unless stated otherwise,all graphs are labelled.Recall that a graph is planar if it admits an embedding in the sphere.We remark that we consider planar graphs as combinatorial objects,without referring to a particular topological embedding.Let g n be the number of planar graphs on n vertices.A superadditivity argu-ment [12]shows that the following limit exists:γ=lim n →∞(g n /n !)1/n .Until recently,the constant γwas known only within certain bounds,namely26.18<γ<30.06.2OMER GIM´ENEZ AND MARC NOYThe lower bound results from the work of Bender,Gao and Wormald[1].They show that,if b n is the number of2-connected planar graphs,then(b n/n!)1/n≈26.18.limn→∞Henceγis at least this value.The upper bound is based on the fact that an unlabelled planar graph on n vertices can be encoded with at mostαn bits for some constantα.If this is the case then g n≤2αn n!,and soγ≤2α.Thefirst such result was obtained by Tur´a n[16] with the valueα=12.This has been improved over the years and presently the best result isα≈4.91,obtained by Bonichon et al.[3].Since24.91≈30.06,the upper bound follows.Recently the present authors[10]were able to obtain,using numerical methods, the approximationγ≈27.2268.In this paper we determineγexactly as an analytic expression.Moreover,wefind a precise asymptotic estimate for the number of planar graphs.Theorem1.Let g n be the number of planar graphs on n vertices.Then (1.1)g n∼g·n−7/2γn n!,where g≈0.4260938569·10−5andγ≈27.2268777685.The constants in the last statement are completely determined as analytic ex-pressions in terms of elementary functions.The proof of Thoerem1,together with the expressions given in the appendix,contain all the necessary details for deter-minining the constants.This also applies to all the remaining constants that appear in the paper.As we show later,for the number c n of connected planar graphs on n vertices, we have the estimatec n∼c·n−7/2γn n!,whereγis as before and c≈0.4104361100·10−5.The proof of Theorem1is based on singularity analysis of generating functions; see[5,6].Let g n,c n and b n be as before.As we show in the next section,there are two equations linking the exponential generating functionsB(x)= b n x n/n!,C(x)= c n x n/n!,G(x)= g n x n/n!.The dominant singularity of B(x)was determined in[1];we are able to obtain the dominant singularities of C(x)and G(x),which are both equal toρ=γ−1.In Section2we review the preliminaries needed for the proof.In Section3 wefind an explicit expression for the generating function B(x,y)of2-connected planar graphs counted according to the number of vertices and edges.This is a key technical result in the paper,which allows us to obtain a full bivariate singular expansion of B(x,y).The explicit expression obtained for the functionβ(x,y,z,w) in the statement of Lemma5suggests that we are in fact integrating a rational function.This is indeed the case as we explain later.In Section4we determine expansions of C(x)and G(x)of square-root type at the dominant singularityρ,and then we apply“transfer theorems”[5,6]to obtain estimates for c n and g n.The singular expansions of C(x)and G(x)can be extended to the corresponding bivariate generating functions C(x,y)and G(x,y)near y=1.This allows us to prove in Section5,using perturbation of singularities[6],a normal limit law forASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS3 the number of edges in random planar graphs.To our knowledge,this problem was first posed in[4].Throughout this paper,we say that a sequence of random variables X n with mean µn and varianceσ2n has a normal limit law if the normalized variables X∗n=(X n−µn)/σn converge in law to the standard normal distribution N(0,1);convergence in law means,as usual,point-wise convergence of the corresponding distribution functions.Theorem2.Let X n denote the number of edges in a random planar graph with n vertices.Then X n is asymptotically normal and the meanµn and varianceσ2n satisfy(1.2)µn∼κn,σ2n∼λn,whereκ≈2.2132652385andλ≈0.4303471697.The same is true,with the same constants,for connected random planar graphs.As a consequence,sinceσn=o(µn),the number of edges is concentrated around its expected value;that is,for everyǫ>0we haveProb{|X n−κn|>ǫn}→0,as n→∞.Previously it had been proved that Prob{X n<αn}→0and Prob{X n>βn}→0, as n→∞,for some constantsαandβ.The best values achieved so far were α≈1.85(shown in[8],improving upon[4])andβ≈2.44(shown in[3],improving upon[14]).Theorem2shows that in fact there is only one constant that matters, namelyκ.The previous theorem shows convergence in distribution to the normal law.How-ever,in this setting it is often the case that one can also prove a local limit law, that is convergence to the density function of the normal law.We prove such a local limit law and we derive large deviation estimates for the number of edges in random planar graphs.In the next statement,as later in the paper,g n,q and c n,q denote respectively the number of planar graphs with n vertices and q edges;ρ(y), G5(y)and C5(y)are computable analytic functions to be introduced later. Theorem3.Letµbe afixed ratio in the open interval(1,3).Take u>0such that−uρ′(u)/ρ(u)=µ.Then,as n goes to∞,(1.3)g n,⌊µn⌋∼n!G5(u)ρ(u)−n u−⌊µn⌋2πnΓ(−5/2)σn7/2,whereσ2=−u2ρ′′(u)ρ(u)+u2ρ′(u)2 nlogg n,⌊µn⌋4OMER GIM´ENEZ AND MARC NOYFigure1.The growth ratio of planar graphs with n vertices and⌊µn⌋edgeswhere u depends onµas in the statement of the theorem.Notice thatλ(µ)is an analytic function ofµ.Figure1shows the plot of exp(λ(µ)),that is,the growth ratio of planar graphs with n vertices and⌊µn⌋edges.The limit of exp(λ(µ))asµ→1is equal to e,which is the growth ratio of labelled trees;the limit asµ→3 is equal to256/27,which is the growth ratio of triangulations[17].(Tutte’s result is for unlabelled triangulations,but a triangulation has at most a linear number ofautomorphisms.)Next we turn our attention to the following problem,considered in[12].LetH be a graph on the vertex set{1,...,h},and let G be a graph on the vertex set {1,...,n},where n>h.Let W⊂V(G)with|W|=h,and let r W denote the least element in W.Following[12],we say that H appears at W in G if(a)theincreasing bijection from{1,...,h}to W gives an isomorphism between H and the induced subgraph G[W]of G;and(b)there is exactly one edge in G between W and the rest of G,and this edge is incident with the root r W.Let a H(G)be the number of appearances of H in G,that is,the number of sets W⊂V(G)such that H appears at W in G.Letαbe(9e2(h+2))−1ρh/h!.It is shown in[12]that if G n is a random planar graph on n vertices thenPr{a H(G n)≤αn}<e−αn,for n large enough.The next result describes more precisely the asymptotic behav-ior of the number of appearances of H in random planar graphs.Theorem4.Let H be afixed rooted connected planar graph with h vertices.Let X n denote the number of appearances of H in a random planar graph with n vertices. Then X n is asymptotically normal and the meanµn and varianceσ2n satisfy (1.4)µn∼ρhASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS5whereρ=γ−1andγis as in Theorem1.Moreover,for everyα<ρn/n!and everyβ>ρn/n!we have for n large enough(1.5)Pr{X n<αn}< uαx(u)ρ n, where x(u)is the solution ofxe(u−1)x k/k!=ρ,and u is related to Z,where Z is eitherαorβ,by the equation−u x′(u)|Aut(H)|·x n|Aut(H)|,6OMER GIM´ENEZ AND MARC NOYwhere Aut(H)is the group of automorphisms of H.In particular,if H is a single vertex,we obtain that the number of isolated vertices in a random planar graph tends to a Poisson law P(ρ)=P(γ−1).This proves a conjecture by McDiarmid, Steger and Welsh[12].As a different application of Theorem7we have the following.Recall that B(x) is the generating function of2-connected planar graphs.Corollary2.Let X n denote the number of connected components which are2-connected in a random planar graph with n vertices.Then X n tend to a Poisson law of parameter B(ρ)≈0.0006837025.We wish to emphasize that the approach that eventually has led to the enumer-ation of planar graphs has a long history.Whitney’s theorem[21]guarantees that a3-connected graph has a unique embedding in the sphere;hence the problem of counting3-connected graphs is in essence equivalent to counting3-connected maps (planar graphs with a specific embedding).This last problem was solved by Mullin and Schellenberg[13]using the approach developed by Tutte in his seminal papers on counting maps(see,for instance,[18]).The next piece is due to Tutte[19]:a 2-connected graph decomposes uniquely into3-connected“components”.Tutte’s decomposition implies equations connecting the generating functions of3-connected and2-connected planar graphs,which were obtained by Walsh[20],using the re-sults of Trakhtenbrot[15].This in turn was used by Bender,Gao and Wormald[1] to solve the problem of counting2-connected planar graphs;their work is most relevant to us and is in fact the starting point of our research.Finally,the decom-position of connected graphs into2-connected components,and the decomposition of arbitrary graphs into connected components,imply equations connecting the cor-responding generating functions.Analytic methods,together with a certain amount of algebraic manipulation,become then the main ingredients in our solution.Acknowledgements.We are grateful to Philippe Flajolet for his encouragement and useful discussions during our research;to Eric Fusy for his help in deriving large deviation estimates and in simplifying thefinal expressions in Lemma5;and to Dominic Welsh for giving us access to an early version of[12].Discussions with Manuel Bodirsky and Mihyun Kang are also acknowledged.2.PreliminariesIn this section and in the rest of the paper we use the language and basic results of Analytic Combinatorics,as in the forthcoming book of Flajolet and Sedgewick[6]. For the sake of completeness,we state the main results we use in this paper(Corol-lary VI.1,Theorems IX.10and IX.13in[6]).Proposition1(Transfer Theorem;simplified version).Assume that f(z)is ana-lytic in a domain∆=∆(φ,R),where R>1,0<φ<π/2and∆(φ,R)={z:z=1,|z|<R,|Arg(z−1)|>φ}.If,as z→1in∆,f(z)∼(1−z)−αthennα−1[z n]f(z)∼ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS7 Proposition2(Quasi-Powers Theorem;algebraic singularities).Let f(z,u)be a bivariate function that is bivariate analytic at(0,0)with nonnegative coefficients there.Assume that f admits in D={|z|≤r}×{|u−1|<ǫ},for some r>0and ǫ>0,the representationf(z,u)=A(z,u)+B(z,u)C(z,u)−α,where A,B and C are analytic in D such that C(z,1)=0has a unique simple root ρ<r in|z|≤r and B(ρ,1)=0.Moreover,neither∂z C(ρ,1)nor∂u C(ρ,1)are0, so there exists a nonconstantρ(u)analytic at u=1such that C(ρ(u),u)=0and ρ=ρ(1).Finally,ρ(u)is such that(2.1)−ρ′′(1)ρ(1)+ ρ′(1)[z n]f(z,1)converges in distribution to a Gaussian variable.The meanµn and the standard deviationσn converge asymptotically toµn andσ√2πnσ)−1.Now we discuss the generating functions that appear in this paper.Recall that g n,c n and b n denote,respectively,the number of planar graphs,connected planar graphs,and2-connected planar graphs on n vertices.The corresponding exponen-tial generating functions are related as follows.Lemma1.The series G(x),C(x)and B(x)satisfy the following equations: G(x)=exp(C(x)),xC′(x)=x exp(B′(xC′(x))),where C′(x)and B′(x)are derivatives with respect to x.Proof.Thefirst equation is standard,given the fact that a planar graph is a set of connected planar graphs,and the set construction in labelled structures corresponds to taking the exponential of the corresponding exponential generating function.The second equation follows from a standard argument on the decomposition of a connected graph into2-connected components.Take a connected graph rooted at a vertex v;hence the generating function xC′(x).Now v belongs to a set of 2-connected components(including single edges),each of them rooted at vertex v; hence the term exp(B′).Finally,in each of the2-connected components,replace every vertex by a rooted connected graph;this explains the substitution B′(xC′(x)). Details can be found,for instance,in[11,p.10].Let b n,q be the number of2-connected planar graphs with n vertices and q edges, and letB(x,y)= b n,q y q x n8OMER GIM´ENEZ AND MARC NOYparameter“number of edges”is additive under taking connected and2-connected components,the previous lemma can be extended as follows.Lemma2.The series G(x,y),C(x,y)and B(x,y)satisfy the following equations:G(x,y)=exp(C(x,y)),x ∂∂xB(x∂1+xy +1(1+U+V)3 ,where U(x,y)and V(x,y)are algebraic functions given by(2.3)U=xy(1+V)2,V=y(1+U)2.In the next result and in the rest of the paper,all logarithms are natural. Lemma3(Bender et al.[1]).We have(2.4)∂B(x,y)2 1+D(x,y)2x2D−log1+D1+xD=0.Moreover,the coefficients of D(x,y)are nonnegative.There is a small modification in equation(2.4)with respect to[1].We must consider the graph consisting of a single edge as being2-connected,otherwise Lem-mas1and2would not hold.Hence the term of lowest degree in the series B(x,y) is yx2/2.Let us comment on the previous equations.The algebraic generating func-tion M corresponds to(rooted)3-connected planar maps.The decomposition of a 2-connected graph into3-connected components implies equations(2.4)and(2.5), The generating function D(x,y)is that of planar networks,which are special graphs with two distinguished vertices.We define the following functions of the complex variable t.The appendix con-tains additional functions that are introduced later.ξ=(1+3t)(1−t)3(1+3t)(1−t)exp −t2(1−t)(18+36t+5t2)(1−t)(1+3t)D2=−48t2(1+t)(1+2t)2(18+6t+t2)ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS 9Let us notice a slight changeinterminology:functionsξand Y are denoted,re-spectively,x 0and y 0in [1];also,we correct a typo,namely a t factor that was missing in the expression for D 2.A key fact is that for y in a suitable small neighborhood of 1,the equation Y (t )=y has a unique solution in t =t (y ).Then define(2.6)R (y )=ξ(t (y )).In the next lemma,D i (y )stands for D i (t (y )).This applies too to functions B i (y )and C i (y )that we introduce later in the paper.Lemma 4(Bender et al.[1]).For fixed y in a small neighborhood of 1,R (y )is the unique dominant singularity of D (x,y ).Moreover,D (x,y )has a branch-point at R (y ),and the singular expansion at R (y )is of the formD (x,y )=D 0(y )+D 2(y )X 2+D 3(y )X 3+O (X 4),where X =2 y 01+D (x,t )2β1(x,y,z )−x 4x +(1+z )log 1+y2+log(1+xz )2(1+w )2−12x log(1+w )+1−4x +2x 2(1−x )(z +w 2+1+w ) .10OMER GIM´ENEZ AND MARC NOY Proof.From equation(3.1)we obtainB(x,y)=x22 y0D(x,t)1+tdt=log(1+y)D(x,y)− y0log(1+t)∂D(x,t)2x2u−xu2∂tdt= D(x,y)0 log(1+s)−xs22x2sds.Thefirst integral has a simple primitive and we are left with an integral involving M(x,y).Summing up we have(3.3)B(x,y)=Θ(x,y,D(x,y))+1sds,whereΘis the elementary functionΘ(x,y,z)=x22z2+(1+z)log1+y2z+1 sds=x D0(1+U)2U(1+U+V)3=W−s1+4xt+4xt2W(1+W)3ds= W(x,D)Q−1−2xt−2xt2 (2Qt−2t−1)ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS11 where for simplicity we write(3.5)Q(x,t)=4x(1+t)2−1+2x(1+t)4x(1+t)2 Q+2x2−4x+1Q−(1−2x−2xt) −12x log(1+t).Finally we have to replace t for W(x,D)in the previous equation.The expression (3.4)and equation(3.5)imply thatQ(x,W(x,D))=1+2x(D+W(x,D)2).Hence when replacing t for W(x,D)we obtain an expression in x,D and W(x,D) that is free of square roots.A routine computation,combined with the intermediate equation(3.3),gives thefinal expression for B(x,y)as claimed.The functionβin the previous lemma looks like the primitive of a rational function.This can be explained as follows(we are grateful to P.Flajolet for this observation).The algebraic equation satisfied by U(here x is considered as a parameter)isu−xy(1+(y(1+u)2)2=0.It can be checked(for instance,using the Maple package algcurves),that this equation in u and y defines a rational curve,that is a curve of genus zero,and so it admits a rational parametrization(u(t),y(t)).Now an integral R(s,U(x,s))ds, where R is a rational function,becomes the integral of a rational function after the change of variables s=y(t).In particular,this applies to the integral in equation(3.3).The former lemma can be used to obtain the singular expansion of B(x,y).The function R(y)is defined in(2.6)and B0,B2,B4,B5are analytic functions of y given in the appendix.Again B i(y)stands for B i(t),where t is the unique solution of Y(t)=y in a neighborhood of1.Lemma6.Forfixed y in a small neighborhood of1,the dominant singularity of B(x,y)is equal to R(y).The singular expansion at R(y)is of the formB(x,y)=B0(y)+B2(y)X2+B4(y)X4+B5(y)X5+O(X6), where X=12OMER GIM´ENEZ AND MARC NOYX3vanish identically in y(or in t).The B i are analytic since they are elementary functions of the D i.4.Asymptotic estimatesIn order to prove Theorem1,first we need to locate the dominant singularity ρ=γ−1of G(x).Since G(x)=exp(C(x)),the functions G(x)and C(x)have the same singularities;hence from now on we concentrate on C(x).We rewrite the second equation in Lemma1as(4.1)F(x)=x exp(B′(F(x))),where F(x)=xC′(x).Notice that the singularities of B′(x)and F(x)are the same, respectively,as those of B(x)and C(x).From(4.1)it follows that(4.2)ψ(u)=ue−B′(u)is the functional inverse of F(x).The dominant singularity ofψis the same as that of B(x),which according to Lemma6is equal to R=R(1).In order to determine the dominant singularityρof F(x),we have to decide which of the following possibilities hold;see Proposition IV.4in[6]for an explanation.(1)There existsτ∈(0,R)(necessarily unique)such thatψ′(τ)=0.Thenψceases to be invertible atτandρ=ψ(τ).(2)We haveψ′(u)=0for all u∈(0,R).Thenρ=ψ(R).The conditionψ′(τ)=0is equivalent to B′′(τ)=1/τ.Since B′′(u)is increasing (the series B(u)has positive coefficients)and1/u is decreasing,we are in case(2) if and only if B′′(R)<1/R.Next we show that this is the case.Claim1.Let R be as before the radius of convergence of B(x).Then B′′(R)<1/R. Proof.Lemma6implies that B′′(R)=2B4/R2(see(4.3)below).Hence the in-equality becomes2B4<R.It holds because R≈0.0381and B4≈0.000767.Let us remark that in a related problem,counting series-parallel graphs,a very similar situation appears but the analogousψfunction does have a maximum in its domain of definition[2].We are now ready for the main result.Proof of Theorem1.As we have seen in the previous claim,the dominant singularity of F(x)is atρ=ψ(R).In order to obtain the singular expansion of F(x)atρ,we have to invert the singular expansion ofψ(u)at R.The expansion of B′(x)follows directly by differentiating the one in Lemma6:(4.3)B′(x)=−12B5X3 +O(X4).Because ofψ(x)=x exp(−B′(x)),by functional composition we obtainψ(x)=Re B2/R 1+ 2B42R X3 +O(X4).Since we are inverting at the singularity,F(x)also has a singular expansion of square-root typeF(x)=F0+F1X+F2X2+F3X3+O(X4),ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS13 with the difference that now X=2B4−R,F3=−52,C5=−2sds=F(x)log x− x0F′(s)log s ds.We change variables t=F(s),so that s=ψ(t)=te−B′(t),and the last integral becomesF(x)logψ(t)dt= F(x)0(log t−B′(t))dt=F(x)log F(x)−F(x)−B(F(x)). HenceC(x)=F(x)log x−F(x)log F(x)+F(x)+B(F(x)).Taking into account that F(ρ)=R and B(R)=B0,we getC0=C(ρ)=R logρ−R log R+R+B0.A simple computation shows that,equivalently,(4.7)C0=R+B0+B2.Thefinal step is simpler since G(x)=e C(x).We apply the exponential function to(4.5)and obtain the singular expansion(4.8)G(x)=e C0 1+C2X2+(C4+11−x/ρ.Again by singularity analysis,we obtain the estimateg n∼g·n−7/2ρ−n n!,where g=e C0c.Finally,sinceρ=ψ(R)=Re−B′(R)and B′(R)=−B2/R,we getρ=Re B2/R,γ=ρ−1=114OMER GIM´ENEZ AND MARC NOYNotice that the probability that a random planar graph is connected is equal toc n/g n∼c/g=e−C0.This result reappears later in Theorem6.5.Gaussian limit lawsThe proofs in this section are based on bivariate singular expansions and per-turbation of singularities.To simplify the notation,in this section we denote by f′(x,y)the derivative of a bivariate function with respect to x.Proof of Theorem2.We rewrite the second equation in Lemma2as(5.1)F(x,y)=x exp(B′(F(x,y),y)),where F(x,y)=xC′(x,y).It follows that,for yfixed,(5.2)ψ(u,y)=ue−B′(u,y)is the functional inverse of F(x,y).We know from the previous section thatψ′(u,y)does not vanish for y=1and u∈(0,R),and thatρ=ψ(R)is the dominant singularity of F(x).Hence by continuity the same is true for y close to1,and the dominant singularity of F(x,y) is at(5.3)ρ(y)=ψ(R(y),y)=R(y)e−B′(R(y),y).Given the analytic expressions for the functions involved,the univariate singular expansion ofψ(x)extends to an expansion ofψ(x,y)for yfixed.The same is true then for F(x,y)and C(x,y),and we obtain a bivariate expansionC(x,y)=C0(y)+C2(y)X2+C4(y)X4+C5(y)X5+O(X6), where the C i(y)are analytic functions,and now X=ρ(1),λ=−ρ′′(1)ρ(1)+ ρ′(1)ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS15 Proof of Theorem3.Consider the generating function C u(x,y)=C(x,uy),where u is afixed constant.In this situation the singularityρu(y)of C u is given byρ(uy), and the associated probabilities p u n,k of C u are(5.4)p u n,k=[y k][x n]C u(x,y)n![x n]C(x,u).In order to apply Proposition3to C u we need to know the singularities of C(x,y) when y is away from1.The following claim extends Claim1and shows that the bivariate singularity expansions given in the proof of Theorem2hold for every y. Claim 2.Let R(y)be the radius of convergence of B(x,y)for yfixed.Then B′′(R(y),y)<1/R(y).Proof.As in the proof of Claim1,it is enough to show that2B4(y)<R(y)for y∈(0,∞);equivalently,that2B4(t)<ξ(t)for t∈(0,1).We bound the logarithm that appears in the expression for B4(see the appendix)aslog 1+t1+2t ≤1+t1+2t−1.Let B4be the function obtained by substituting the logarithm in B4for the right-hand side in the previous inequality.Then it is enough to show that2 B4(t)<ξ(t)for t∈(0,1).Since both B4andξare rational functions,the problem reduces to showing that a certain polynomial(in fact,of degree20)with integer coefficients has no root in(0,1).We have checked that this is indeed the case using Maple.Another requirement is thatρ(z)attains uniquely its minimum on|z|=u at z=u.Suppose it exists w=u with|w|=u such that|ρ(w)|≤ρ(u).It follows from(5.3)that R(z)is equal to F(ρ(z),z),and since F(x,y)has non-negative coefficients,|R(w)|=|F(ρ(w),w)|≤F(ρ(u),u)=R(u).However,this contradicts the fact that R(z)attains uniquely its minimum on|z|=u at z=u,as shown in[1,Lemma3].Now Proposition3applied to C u yields(5.5)p u n,⌊µ(u)n⌋∼12πnσ(u),whereµ(u)areσ(u)are given byµ(u)=−ρ′u(1)ρ(u),σ(u)2=−ρ′′u(1)ρu(1)+ ρ′u(1)ρ(u)−uρ′(u)ρ(u) 2.Theorem3follows by combining equations(5.4)and(5.5)for k=⌊µ(u)n⌋and using the asymptotic expression of[x n]C(x,y)for y=u.The valueµis constrained to the interval(1,3)since lim u→0µ(u)=1and lim u→∞µ(u)=3.Proof of Theorem4.Let us recall Equation(4.1)F(x)=x exp(B′(F(x))),16OMER GIM ´ENEZ AND MARC NOYwhere F (x )=xC ′(x )is the generating function of rooted connected planar graphs.In order to mark appearances of H ,we have to look at the root r of a rooted connected graph G ,and the blocks to which it belongs;recall this is encoded in the term exp(B ′(F (x ))).We are interested in the blocks which are equal to a single edge rv ,and within these blocks to the situation where vertex v is substituted by a copy of H .In this case we mark an appearance of H with the secondary variable y .If we let f (x,y )be the corresponding generating function,then the previous discussion translates into the equation (5.6)f (x,y )=x exp B ′(f (x,y ))+(y −1)x h (h −1)!f (x,y ).Since f (x,y )and g (x,y )have the same dominant singularity for any fixed y it does not matter which one we choose for singularity analysis;hence in the rest of the proof we work with f (x,y ),defined through (5.6).Equation (5.6)can be rewritten asf (x,y )=ζ(x,y )exp (B ′(f (x,y ))),where ζ(x,y )=x exp((y −1)x h /h !).Comparing the previous equation with (4.1),it follows thatf (x,y )=F (ζ(x,y )).Given that ρis the dominant singularity of F (x ),the dominant singularity of f (x,y )for fixed y is the smallest value τ(y )satisfying (5.7)ζ(τ(y ),y )=τ(y )exp (y −1)τ(y )hτ(1)=ρhτ(1)−τ′(1)τ(1) 2=ρ.From the singular expansion of F (x )at ρ,we derive a corresponding bivariate singular expansion of f (x,y )at τ(y ),and again a normal limit law follows from Proposition 2.As in the previous proof,a large deviation estimate also follows,and from this we obtain the bounds in (1.5);the details are omitted to avoid repetition.ASYMPTOTIC ENUMERATION AND LIMIT LA WS OF PLANAR GRAPHS17 Proof of Theorem5.The proof is similar to the previous proofs,and so we omit some details.The generating function C1(x,y)of connected planar graphs according to the number of vertices and blocks satisfies the equationxC′1(x,y)=x exp(y B′(xC′1(x,y))),where B(x)is the univariate generating function of2-connected planar graphs.Let F1(x,y)=xC′1(x,y).Then,for yfixed,ψ1(u,y)=ue−yB′(u)is the functional inverse of F1(x,y).The dominant singularity ofψ1(u,y)is at R, which in this case is independent of y,and the dominant singularity of F1(x,y)is atρ1(y)=ψ1(R,y)=Re−yB′(R).Again we have bivariate singular expansions whose coefficients are analytic func-tions of y,and the quasi-powers theorem implies asymptotic normality of the param-eter.The asymptotic expressions for the expected value and variance are obtained as before,but in this case the computations are particularly easy,sinceρ′1(y)=−ρ1(y)B′(R).We know thatρ=ψ(R)=Re−B′(R),henceζ=−ρ′1(1)ρ1(1)−ρ′1(1)ρ1(1)2=B′(R)=ζ.6.Poisson limit lawsAs opposed to the proofs in the previous section,to prove Theorems6and7, univariate asymptotics is enough.Proof of Theorem6.Letν=C(ρ)=C0,the evaluation of C(x)at its dominant singularity.Forfixed k,the generating function of planar graphs with exactly k connected components is1[x n]G(x)∼kC k−1(k−1)!e−ν,as was to be proved. Proof of Theorem7.The proof is similar to the previous one.The generating function of planar graphs with no component belonging to A is exp(C(x)−A(x)). Hence the generating function of planar graphs with exactly k components in A is 1k!A(x)k e−A(x)G(x).。

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