《SAS数据分析范例》(SAS数据集)
sas数据分析报告
sas数据分析报告摘要：本文介绍了基于SAS软件进行的数据分析报告。
首先，对数据进行了简要的介绍和处理，并对数据进行了可视化处理。
然后我们使用SAS建立了模型，并对模型进行了评估。
最后，我们对结果进行了解释和分析，并提出了相关的建议。
关键词：SAS，数据分析，模型建立，可视化，结果解释1. 简介SAS是一款广泛应用于数据分析领域的统计软件，其丰富的统计函数和数据可视化功能使得它成为了数据分析师不可或缺的工具。
本文使用SAS对某公司的销售数据进行分析，以帮助公司管理者更好地了解企业的经营情况和预测未来的发展趋势。
2. 数据处理与可视化我们先对数据进行了初步的清理和整理，去除了缺失值和异常值，并对数据进行了标准化处理。
然后，我们使用SAS的数据可视化功能对数据进行了可视化处理，包括制作散点图、直方图和箱线图等，以便更好地了解数据的分布情况和相关性。
3. 模型建立与评估我们基于数据建立了模型，并使用SAS对模型进行了评估。
在模型建立过程中，我们采用了多元线性回归模型，考虑了各个变量之间的相互关系和影响。
在模型评估过程中，我们采用了交叉验证和R方值等指标，对模型的预测能力进行了评估。
4. 结果解释与分析根据模型的预测结果，我们对数据进行了解释和分析，并提出了相关的建议。
我们确定了销售额、广告投放、促销活动等因素对销售额的影响，根据模型结果提出了优化销售策略的建议。
同时，我们进一步分析了销售额的趋势，预测了未来的销售情况，为公司的经营决策提供了有力的支持。
结论：本文基于SAS进行了数据分析报告，利用SAS的数据处理、可视化、模型建立和评估等功能，全面分析了某公司的销售数据。
通过对数据的解释和分析，我们提出了相关的建议，为公司的经营决策提供了参考。
这表明SAS在数据分析领域的应用效果显著，对于企业的发展和决策具有重要的意义。
数据分析SAS报告
x1
1.00000
0.86989 0.0243
-0.39630 0.4367
0.85207 0.0312
-0.98052 0.0006
-0.68122 0.1362
-0.99182 0.0001
-0.61478 0.1940
x2
0.86989 0.0243
1.00000
-0.00355 0.9947
Difference
Proportion
Cumulative
1 2 3 4 5 6 7 8
5.89746633 1.61037380 0.35740580 0.11750526 0.01724881 0.00000000 0.00000000 0.00000000
4.28709253 1.25296800 0.23990054 0.10025645 0.01724881 0.00000000 0.00000000
-.9918 -.8632 0.3532 -.8635 0.9862 0.6901 1.0000 0.5706
-.6148 -.8798 -.1698 -.7722 0.5292 0.8685 0.5706 1.0000
Eigenvalues of the Correlation Matrix
Eigenvalue
4.796666667 0.381663028
6.536666667 3.902002904
8.998333333 2.293359254
5.258333333 1.648179804
2.026666667 0.781733117
Correlation Matrix
x1
x2
x3
SAS数据分析教程说明书
About the T utorialSAS is a leader in business analytics. Through innovative analytics, it caters to business intelligence and data management software and services. SAS transforms data into insight which can give a fresh perspective to business.Unlike other BI tools available in the market, SAS takes an extensive programming approach to data transformation and analysis rather than a drag-drop-connect approach. This makes it stand out from the crowd with enhanced control over data manipulation. SAS has a very large number of components customized for specific industries and data analysis tasks.AudienceThis tutorial is designed for all those readers who want to read and transform raw data to produce insights for business using SAS. Readers who aspire to become Data Analysts or Data Scientists can also draw benefits from this tutorial.PrerequisitesBefore proceeding with this tutorial, you should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages will help you understand the SAS programming concepts. Familiarity with SQL will be an added benefit.Disclaimer & CopyrightCopyright 2016 by Tutorials Point (I) Pvt. Ltd.All the content and graphics published in this e-book are the property of Tutorials Point (I) Pvt. Ltd. The user of this e-book is prohibited to reuse, retain, copy, distribute or republish any contents or a part of contents of this e-book in any manner without written consent of the publisher.We strive to update the contents of our website and tutorials as timely and as precisely as possible, however, the contents may contain inaccuracies or errors. Tutorials Point (I) Pvt. Ltd. provides no guarantee regarding the accuracy, timeliness or completeness of our website or its contents including this tutorial. If you discover any errors on our website or inthistutorial,******************************************.T able of ContentsAbout the Tutorial (i)Audience (i)Prerequisites (i)Disclaimer & Copyright (i)Table of Contents (ii)1.SAS – Overview (1)Uses of SAS (1)Types of SAS Software (3)Libraries in SAS (4)2.SAS – Environment (5)Download SAS University Edition (5)The SAS Environment (14)3.SAS – User Interface (15)SAS Main Window (15)Code Autocomplete (16)Program Execution (16)Program Log (17)Program Result (17)Program Tabs (18)4.SAS – Program Structure (22)SAS Program Structure (22)DATA Step (22)PROC Step (23)The OUTPUT Step (23)The Complete SAS Program (24)Program Output (24)5.SAS – Basic Syntax (26)SAS Statements (26)SAS Variable Names (26)SAS Data Set (27)SAS File Extensions (27)Comments in SAS (28)6.SAS – Data Sets (29)SAS Built-In Data Sets (29)Importing External Data Sets (31)7.SAS – Variables (35)SAS Variable Types (35)Use of Variables in SAS Program (36)Using the Variables (37)8.SAS – Strings (39)Declaring String Variables (39)String Functions (40)Accessing Array Values (44)Using the OF operator (44)Using the IN operator (45)10.SAS – Numeric Formats (47)Reading Numeric formats (47)Displaying Numeric formats (48)11.SAS – Operators (50)Arithmetic Operators (50)Logical Operators (51)Comparison Operators (52)Minimum/Maximum Operators (53)Concatenation Operator (54)Operators Precedence (55)12.SAS – Loops (56)Flow Diagram (56)SAS – DO Index Loop (57)SAS – DO WHILE Loop (58)SAS – DO UNTIL Loop (59)13.SAS – Decision Making (60)SAS – IF Statement (61)SAS − IF THEN ELSE Statement (63)SAS − IF THEN ELSE IF Statement (65)SAS − IF-THEN-DELETE Statement (66)14.SAS − Functions (68)Function Categories (68)Mathematical Functions (68)Date and Time Functions (69)Character Functions (70)Truncation Functions (71)Miscellaneous Functions (72)15.SAS − Input Methods (74)List Input Method (74)Named Input Method (75)Column Input Method (76)Formatted Input Method (77)16.SAS – Macros (79)Macro Variables (79)Local Macro Variable (80)Macro Programs (81)Commonly Used Macros (82)Macro % RETURN (83)Macro % END (84)SAS Date Informat (86)SAS Date output format (87)SAS DATA SET OPERATIONS (88)18.SAS − Read Raw Data (89)Reading ASCII (Text) Data Set (89)Reading Delimited Data (90)Reading Excel Data (91)Reading Hierarchical Files (92)19.SAS − Write Data Sets (94)PROC EXPORT (94)Writing a CSV file (95)Writing a Tab Delimited File (96)20.SAS − Concatenate Data Sets (97)21.SAS − Merge Data Sets (103)Data Merging (103)22.SAS − Subsetting Data Sets (107)Subsetting Variables (107)Subsetting Observations (109)23.SAS − Sort Data Sets (111)Reverse Sorting (112)Sorting Multiple Variables (113)24.SAS − Format Data Sets (115)Using PROC FORMAT (116)25.SAS − SQL (118)SQL Create Operation (118)SQL Read Operation (119)SQL SELECT with WHERE Clause (120)SQL UPDATE Operation (121)SQL DELETE Operation (123)26.SAS − ODS (124)Creating HTML Output (124)Creating PDF Output (126)Creating TRF(Word) Output (127)27.SAS − Simulations (129)SAS DATA REPRESENTATION (130)28.SAS − Histograms (131)Simple Histogram (131)Histogram with Curve Fitting (132)29.SAS − Bar Charts (134)Simple Bar chart (134)Stacked Bar chart (135)Clustered Bar chart (136)30.SAS − Pie Charts (138)Simple Pie Chart (138)Pie Chart with Data Labels (140)Grouped Pie Chart (142)31.SAS − Scatter Plots (144)Simple Scatterplot (144)Scatterplot with Prediction (145)Scatter Matrix (147)32.SAS − Boxplots (148)Simple Boxplot (148)Boxplot in Vertical Panels (150)Boxplot in Horizontal Panels (150)SAS BASIC STATISTICAL PROCEDURE (152)33.SAS ─ Arithmetic Mean (153)Mean of a Dataset (153)Mean of Select Variables (154)Mean by Class (155)34.SAS ─ Standard Deviation (156)Using PROC MEANS (156)Using PROC SURVEYMEANS (157)Using BY Option (159)35.SAS ─ Frequency Distributions (161)Single Variable Frequency Distribution (161)Multiple Variable Frequency Distribution (163)Frequency Distribution with Weight (164)36.SAS ─ Cross Tabulations (165)Cross Tabulation of 3 Variables (166)Cross Tabulation of 4 Variables (167)37.SAS ─ T-tests (169)Paired T-test (170)Two Sample T-test (172)38.SAS ─ Correlation Analysis (173)Correlation Between All Variables (175)Correlation Matrix (176)39.SAS ─ Linear Regression (177)40.SAS ─ Bland-Altman Analysis (180)Enhanced Model (182)41.SAS ─ Chi-Square (184)Two-Way Chi-Square (186)42.SAS ─ Fisher's Exact Tests (188)Applying Fisher Exact Test (188)43.SAS ─ Repeated Measure Analysis (190)44.SAS — One Way Anova (193)Applying ANOVA (193)Applying ANOVA with MEANS (194)45.SAS ─ Hypothesis Testing (196)1.SASSAS stands for Statistical Analysis Software. It was created in the year 1960 by the SAS Institute. From 1st January 1960, SAS was used for data management, business intelligence, Predictive Analysis, Descriptive and Prescriptive Analysis etc. Since then, many new statistical procedures and components were introduced in the software.With the introduction of JMP (Jump) for statistics, SAS took advantage of the graphical user interface (GUI) which was introduced by the Macintosh. Jump is basically used for applications like Six Sigma, designs, quality control and engineering and scientific analysis. SAS is platform independent which means you can run SAS on any operating system either Linux or Windows. SAS is driven by SAS programmers who use several sequences of operations on the SAS datasets to make proper reports for data analysis.Over the years SAS has added numerous solutions to its product portfolio. It has solution for Data Governance, Data Quality, Big Data Analytics, Text Mining, Fraud management, Health science etc. We can say that SAS has a solution for every business domain.To have a glance at the list of products available you can visit SAS Components. Uses of SASSAS is basically worked on large datasets. With the help of SAS software, you can perform various operations on data. Some of the operations include:∙Data management∙Statistical analysis∙Report formation with perfect graphics∙Business planning∙Operations research and project management∙Quality improvement∙Application development∙Data extraction∙Data transformation∙Data updation and modificationIf we talk about the components of SAS, then more than 200 components are available in SAS.T ypes of SAS SoftwareLet us now understand the different types of SAS software.∙Windows or PC SAS∙SAS EG (Enterprise Guide)∙SAS EM (Enterprise Miner i.e. for Predictive Analysis)∙SAS Means∙SAS StatsWe use Windows SAS in large organizations and also in training institutes. A few organizations also use Linux but there is no graphical user interface so you have to write code for every query. In Window SAS, there are a lot of utilities available that help the programmers and also reduce the time of writing the codes.A SaS Window has 5 parts.SASLibraries in SASLibraries are storage locations in SAS. You can create a library and save all the similar programs in that library. SAS provides you the facility to create multiple libraries. A SAS library is only 8 characters long.There are two types of libraries available in SAS:2.SASSAS Institute Inc. has released a free SAS University Edition. This provides a platform for learning SAS programming. It provides all the features that you need to learn in BASE SAS programming which in turn enables you to learn any other SAS component.The process of downloading and installing SAS University Edition is very simple. It is available as a virtual machine which needs to be run on a virtual environment. You need to have virtualization software already installed in your PC before you can run the SAS software. In this tutorial, we will be using VMware. The following are the details of the steps to download, setup the SAS environment and verify the installation.Download SAS University EditionSAS University Edition is available for download at the URL SAS University Edition. Please scroll down to read the system requirements before you begin the download. The following screen appears on visiting this URL.Setup virtualization softwareScroll down on the same page to locate the installation step 1. This step provides the links to get the suitable virtualization software. In case you already have any one of these software installed in your system, you can skip this step.Quick start virtualization softwareIn case you are completely new to the virtualization environment, you can familiarize yourself with it by going through the following guides and videos available as step 2. You can skip this step in case you are already familiar.Download the Zip fileIn step 3, you can choose the appropriate version of the SAS University Edition compatible with the virtualization environment you have. It downloads as a zip file with the name similar to unvbasicvapp__9411005__vmx__en__sp0__1.zipUnzip the Zip fileThe zip file above needs to be unzipped and stored in an appropriate directory. In our case, we have chosen the VMware zip file which shows the following files after unzipping.Start the VMware player (or workstation) and open the file which ends with an extension. vmx. The following screen appears. Please notice the basic settings like memory and hard disk space allocated to the vm.Click the Power on this virtual machine alongside the green arrow mark to start the virtual machine. The following screen appears.The following screen appears when the SAS vm is in the state of loading after which the running vm gives a prompt to go to a URL location that will open the SAS environment.Starting SAS studioOpen a new browser tab and load the above URL (which differs from one PC to another). The following screen appears indicating the SAS environment is ready.SASThe SAS EnvironmentOn clicking the Start SAS Studio, we get the SAS environment which by default opens in the visual programmer mode as shown in the following screenshot.We can also change it to the SAS programmer mode by clicking on the dropdown.We are now ready to write the SAS Programs.3.SASSAS Programs are created using a user interface known as SAS Studio. In this chapter, we will discuss the various windows of SAS User Interface and their usage.SAS Main WindowThis is the window you see on entering the SAS environment. The Navigation Pane is to the left. It is used to navigate various programming features. The Work Area is to the right. It is used for writing the code and executing it.Code AutocompleteThis feature helps in getting the correct syntax of the SAS keywords and also provides link to the documentation for the keywords.Program ExecutionThe execution of code is done by pressing the run icon, which is the first icon from left or the F3 button.Program LogThe log of the executed code is available under the Log tab. It describes the errors, warnings or notes about the program’s execution. This is the window where you get all the clues to troubleshoot your code.Program ResultThe result of the code execution is seen in the RESULTS tab. By default, they are formatted as html tables.End of ebook previewIf you liked what you saw…Buy it from our store @ https://。
SAS数据分析工具介绍
SAS数据分析工具介绍随着数字化时代的到来，数据分析成为了企业和组织的必修课。
其中，SAS数据分析工具作为全球最为知名的商业分析软件之一，备受广大企业和分析师的青睐。
本文将对SAS数据分析工具进行介绍，包括其特点、应用领域以及使用技巧等方面。
一、SAS数据分析工具特点SAS数据分析工具全称Statistical Analysis System，是由SAS 公司开发的商业分析软件。
其最为显著的特点是其全面的功能性，包括数据管理、统计分析、建模和数据可视化等多个方面。
SAS公司提供多种产品包，以满足不同行业用户的需求。
同时，SAS数据分析工具的语法清晰、规范，并且具有高度的灵活性，能够快速响应用户的分析需求。
基于这些优点，SAS数据分析工具成为了金融、保险、医疗、航空航天等多个行业的分析工具之一。
二、SAS数据分析工具应用领域1. 金融领域金融行业是SAS数据分析工具的主要应用领域之一。
通过SAS 的数据管理、预测建模和可视化等功能，可以实现金融产品的风险管理和营销等方面的应用。
例如，银行可以利用SAS数据分析工具进行授信风险评估、客户身份识别等工作；投资机构可以通过SAS数据分析工具对市场波动进行预测，为投资策略做出决策。
2. 医疗领域医疗行业是另一个SAS数据分析工具的主要应用领域。
医疗机构可以利用SAS数据分析工具对大量的病历数据进行分析，在医疗管理、疾病预测等方面提供帮助。
例如，一些医疗保险公司可以利用SAS数据分析工具进行预测分析，提前预测疾病风险，避免大量的医疗费用支出。
3. 交通领域在航空和铁路等交通领域也有SAS数据分析工具的应用。
航空公司可以利用SAS数据分析工具对飞行数据进行分析，预测飞行状态，并且提高飞行效率。
铁路公司可以利用SAS数据分析工具对列车状态进行监控，在列车故障和延误时作出快速处理。
三、SAS数据分析工具的使用技巧1.了解基础知识使用SAS数据分析工具需要具备相应的基础知识，包括统计学、数学和计算机等相关的知识。
《SAS大数据分析报告范例》(SAS大数据集)
《SAS数据分析范例》数据集目录表1 sas.bd1 (4)表2 sas.bd3 (5)表3 sas.bd4 (6)表4 sas.belts (7)表5 sas.c1d2 (8)表6 sas.c7d31 (10)表7 sas.dead0 (11)表8 sas.dqgy (11)表9 sas.dqjyjf (12)表10 sas.dqnlmy3 (13)表11 sas.dqnlmy (14)表12 sas.dqrjsr (15)表13 sas.dqrk (16)表14 sas.gjxuexiao0 (17)表15 sas.gnsczzgc (19)表16 sas.gnsczzs (19)表17 sas.gr08n01 (20)表18 sas.iris (22)表19 sas.jmcxck0 (23)表20 sas.jmjt052 (23)表22 sas.jmjt054 (25)表23 sas.jmjt055 (26)表24 sas.jmxfsps (27)表25 sas.jmxfspzs0 (28)表26 sas.jmxfzss (29)表27 sas.jmxfzst (30)表28 sas.kscj2 (31)表29 sas.modeclu4 (33)表30 sas.ms8d1 (33)表31 sas.nlmyzzs (34)表32 sas.plates (36)表33 sas.poverty (37)表34 sas.rjnycpcl0 (38)表35 sas.rjsrs (38)表36 sas.sanmao (40)表37 sas.sczz1 (41)表38 sas.sczz06s (41)表39 sas.sczz (43)表40 sas.sczzgc1 (44)表41 sas.sczzgc (45)表42 sas.slgong (46)表44 sas.wire (48)表45 sas.xucps (48)表46 sas.zyncpcl1s (48)表47 sas.zyncpcl2 (49)表48 sas.zyncpcl3 (49)表1 sas.bd1表2 sas.bd3表3 sas.bd4表4 sas.belts表5 sas.c1d2表6 sas.c7d31表7 sas.dead0表8 sas.dqgy表9 sas.dqjyjf表10 sas.dqnlmy3表11 sas.dqnlmy表12 sas.dqrjsr表13 sas.dqrk表14 sas.gjxuexiao0表15 sas.gnsczzgc表16 sas.gnsczzs表17 sas.gr08n01表18 sas.iris表19 sas.jmcxck0表20 sas.jmjt052表21 sas.jmjt053表22 sas.jmjt054表23 sas.jmjt055表24 sas.jmxfsps表25 sas.jmxfspzs0表26 sas.jmxfzss表27 sas.jmxfzst表28 sas.kscj2表29 sas.modeclu4表30 sas.ms8d1表31 sas.nlmyzzs表35 sas.rjsrs表36 sas.sanmao表37 sas.sczz1表38 sas.sczz06s表39 sas.sczz表45 sas.xucps表46 sas.zyncpcl1s表47 sas.zyncpcl2表48 sas.zyncpcl3。
SAS数据分析实验报告
SAS数据分析实验报告摘要：本文使用SAS软件对一组数据集进行了分析。
通过数据清洗、数据变换、数据建模和数据评估等步骤，得出了相关的结论。
实验结果表明，使用SAS软件进行数据分析可以有效地处理和分析大型数据集，得出可靠的结论。
1.引言数据分析在各个领域中都扮演着重要的角色，可以帮助人们从大量的数据中提取有用信息。
SAS是一种常用的数据分析软件，被广泛应用于统计分析、商业决策、运营管理等领域。
本实验旨在探究如何使用SAS软件进行数据分析。
2.数据集描述本实验使用了一个包含1000个样本的数据集。
数据集包括了各个样本的性别、年龄、身高、体重等多种变量。
3.数据清洗在进行数据分析之前，首先需要对数据进行清洗。
数据清洗包括缺失值处理、异常值处理和重复值处理等步骤。
通过使用SAS软件中的相应函数和命令，我们对数据集进行了清洗，确保数据的质量和准确性。
4.数据变换在进行数据分析之前，还需要对数据进行变换。
数据变换包括数据标准化、数据离散化和数据归一化等操作。
通过使用SAS软件中的变换函数和操作符，我们对数据集进行了变换，使其符合分析的需要。
5.数据建模数据建模是数据分析的核心过程，包括回归分析、聚类分析和分类分析等。
在本实验中，我们使用SAS软件的回归、聚类和分类函数，对数据集进行了建模分析。
首先，我们进行了回归分析，通过拟合回归模型，找到了自变量对因变量的影响。
通过回归模型，我们可以预测因变量的值，并分析自变量的影响因素。
其次，我们进行了聚类分析，根据样本的特征将其分类到不同的群组中。
通过聚类分析，我们可以发现样本之间的相似性和差异性，从而做出针对性的决策。
最后，我们进行了分类分析，根据样本的特征判断其所属的类别。
通过分类分析，我们可以根据样本的特征预测其所属的类别，并进行相关的决策。
6.数据评估在进行数据分析之后，还需要对结果进行评估。
评估包括模型的拟合程度、变量的显著性和模型的稳定性等。
通过使用SAS软件的评估函数和指标，我们对数据分析的结果进行了评估。
数据分析(SAS描述性统计分析过程)
var
变量列表 ;
by
变量列表 ;
freq
变量 ;
weight 变量 ;
id
变量列表 ;
output <out=输出数据集名> <统计量关键字=变量名列表> <pctlpts= 百分位数 pctlpre=变量前缀名 pctlname=变量后缀名>;
run;
proc uiate过程旳主要控制语句如下：
proc means（5）
SAS程序 data examp1; input x @@; cards; 70.4 72.0 76.5 74.3 76.5 77.6 67.3 72.0 75.0 74.3 73.5 79.5 73.5 74.7 65.0 76.5 81.6 75.4 72.7 72.7 67.2 76.5 72.7 70.4 77.2 68.8 67.3 67.3 67.3 72.7 75.8 73.5 75.0 72.7 73.5 73.5 72.7 81.6 70.3 74.3 73.5 79.5 70.4 76.5 72.7 77.2 84.3 75.0 76.5 70.4 ; proc means data=examp1 n mean cv skewness kurtosis range median ; var x; run;
mode sumwgt max min range median t prt clm lclm uclm
众数，出现频数最高旳数 权数和 最大值 最小值 极差，max—min 中间值 总体均值等于0旳t统计量 t分布旳双尾p值 置信度上限和下限
置信度下限
置信度上限
kurtosis
对尾部陡平旳度量——峰度
------Quantile-----Percent Observed Estimated
《生物统计》SAS分析示例
02
可以使用PROC MEANS计算单个变量的描述性统计量，也可以
同时计算多个变量的描述性统计量。
可以通过输出选项选择所需的描述性统计量，并按照指定的格
03
式显示结果。
使用PROC FREQ进行描述性统计分析
01
PROC FREQ过程用于对分类数据进行描述性统计分析，如计算频数、频率、相 对频数等。
输出结果包括组间和组内的方差分析表、效应量估计等，用于评估不同组 别之间的差异和效应量大小。
05
高级统计分析在SAS中的实 现
主成分分析
主成分分析是一种降维技术，用于减少变量的 数量，同时尽可能保留原始数据中的变异。
在SAS中，可以使用PROC PRINCOMP过程进 行主成分分析，该过程可以计算主成分、输出 相关矩阵和方差矩阵等。
02
可以使用PROC FREQ对单个分类变量进行分析，也可以对多个分类变量进行分 析。
03
可以通过输出选项选择所需的描述性统计量，并按照指定的格式显示结果。同 时，还可以生成各类统计图形，如条形图、饼图等，以便更直观地展示分类数 据的分布情况。
04
推论性统计分析在SAS中的 实现
推论性统计分析的定义和目的
定义
推论性统计分析是基于样本数据来推 断总体特性的统计方法。
目的
通过对样本数据的分析，获取有关总 体特性的信息，并对总体进行假设检 验和预测。
使用PROC REG进行线性回归分析
1
线性回归分析是一种常用的推论性统计分析方法， 用于研究自变量与因变量之间的线性关系。
2
在SAS中使用PROC REG进行线性回归分析，可 以通过指定自变量和因变量来拟合线性回归模型。
进行这些高级统计分析，并得到准确的结果解释。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
《SAS数据分析范例》数据集
目录
表1 sas.bd1 (3)
表2 sas.bd3 (4)
表3 sas.bd4 (5)
表4 sas.belts (6)
表5 sas.c1d2 (7)
表6 sas.c7d31 (8)
表7 sas.dead0 (9)
表8 sas.dqgy (10)
表9 sas.dqjyjf (11)
表10 sas.dqnlmy3 (12)
表11 sas.dqnlmy (13)
表12 sas.dqrjsr (14)
表13 sas.dqrk (15)
表14 sas.gjxuexiao0 (16)
表15 sas.gnsczzgc (17)
表16 sas.gnsczzs (18)
表17 sas.gr08n01 (19)
表18 sas.iris (20)
表19 sas.jmcxck0 (21)
表20 sas.jmjt052 (22)
表21 sas.jmjt053 (23)
表22 sas.jmjt054 (24)
表23 sas.jmjt055 (25)
表24 sas.jmxfsps (26)
表25 sas.jmxfspzs0 (27)
表26 sas.jmxfzss (28)
表27 sas.jmxfzst (29)
表28 sas.kscj2 (30)
表29 sas.modeclu4 (31)
表30 sas.ms8d1 (32)
表31 sas.nlmyzzs (33)
表32 sas.plates (34)
表33 sas.poverty (35)
表34 sas.rjnycpcl0 (36)
表35 sas.rjsrs (37)
表36 sas.sanmao (38)
表37 sas.sczz1 (39)
表38 sas.sczz06s (40)
表39 sas.sczz (41)
表40 sas.sczzgc1 (42)
表41 sas.sczzgc (43)
表42 sas.slgong (44)
表43 sas.spls0 (45)
表44 sas.wire (46)
表45 sas.xucps (47)
表46 sas.zyncpcl1s (47)
表47 sas.zyncpcl2 (48)
表48 sas.zyncpcl3 (48)
表1 sas.bd1
表2 sas.bd3
表3 sas.bd4
表4 sas.belts
表5 sas.c1d2
表6 sas.c7d31
表7 sas.dead0
表8 sas.dqgy
表9 sas.dqjyjf
表10 sas.dqnlmy3
表11 sas.dqnlmy
表12 sas.dqrjsr
表13 sas.dqrk
表14 sas.gjxuexiao0
表15 sas.gnsczzgc
表16 sas.gnsczzs
表17 sas.gr08n01
表18 sas.iris
表19 sas.jmcxck0
表20 sas.jmjt052
表21 sas.jmjt053
表22 sas.jmjt054
表23 sas.jmjt055
表24 sas.jmxfsps
表25 sas.jmxfspzs0
表26 sas.jmxfzss
表27 sas.jmxfzst
表28 sas.kscj2
表29 sas.modeclu4
表30 sas.ms8d1
表31 sas.nlmyzzs
表32 sas.plates
表33 sas.poverty
表34 sas.rjnycpcl0
表35 sas.rjsrs
表36 sas.sanmao
表37 sas.sczz1
表38 sas.sczz06s
表39 sas.sczz
表40 sas.sczzgc1
表41 sas.sczzgc
表42 sas.slgong
表43 sas.spls0
表44 sas.wire
表45 sas.xucps
表46 sas.zyncpcl1s
表47 sas.zyncpcl2 表48 sas.zyncpcl3。