数据模型与决策课程大作业
数据模型与决策课程大作业(完整资料).doc
【最新整理，下载后即可编辑】数据模型与决策课程大作业以我国汽油消费量为因变量，乘用车销量、城镇化率和90#汽油吨价与城镇居民人均可支配收入的比值为自变量时行回归（数据为年度时间序列数据）。
试根据得到部分输出结果，回答下列问题：1）“模型汇总表”中的R方和标准估计的误差是多少？2）写出此回归分析所对应的方程；3）将三个自变量对汽油消费量的影响程度进行说明；4）对回归分析结果进行分析和评价，指出其中存在的问题。
1）“模型汇总表”中的R方和标准估计的误差是多少？答案：R方为0.993^2=0.986 ；标准估计的误差为120910.147^（0.5）=347.722）写出此回归分析所对应的方程；答案：假设汽油消费量为Y，乘用车销量为a，城镇化率为b，90#汽油吨价/城镇居民人均可支配收入为c,则回归方程为：Y=240.534+0.00s027a+8649.895b-198.692c3）将三个自变量对汽油消费量的影响程度进行说明；乘用车销量对汽油消费量相关系数只有0.00027，数值太小，几乎没有影响，但是城镇化率对汽油消费量相关系数是8649.895，具有明显正相关，当城镇化率每提高1，汽油消费量增加8649.895。
乘用90#汽油吨价/城镇居民人均可支配收入相关系数为-198.692，呈明显负相关，即乘用90#汽油吨价/城镇居民人均可支配收入每增加1个单位，汽油消费量降低198.692个单位。
a, b, c三个自变量的sig值为0.000、0.000、0.009，在显著性水平0.01情形下，乘用车消费量对汽油消费量的影响显著为正。
（4）对回归分析结果进行分析和评价，指出其中存在的问题。
在学习完本课程之后，我们可以统计方法为特征的不确定性决策、以运筹方法为特征的策略的基本原理和一般方法为基础，结合抽样、参数估计、假设分析、回归分析等知识对我国汽油消费量影响因素进行了模拟回归，并运用软件计算出回归结果，故根据回归结果，对具体回归方程，回归准确性，自变量影响展开分析。
数据模型与决策习题与参考答案
数据模型与决策习题与参考答案《数据模型与决策》复习题及参考答案第⼀章绪⾔⼀、填空题1．运筹学的主要研究对象是各种有组织系统的管理问题，经营活动。
2．运筹学的核⼼是运⽤数学⽅法研究各种系统的优化途径及⽅案，为决策者提供科学决策的依据。
3．模型是⼀件实际事物或现实情况的代表或抽象。
4、通常对问题中变量值的限制称为约束条件，它可以表⽰成⼀个等式或不等式的集合。
5．运筹学研究和解决问题的基础是最优化技术，并强调系统整体优化功能。
运筹学研究和解决问题的效果具有连续性。
6．运筹学⽤系统的观点研究功能之间的关系。
7．运筹学研究和解决问题的优势是应⽤各学科交叉的⽅法，具有典型综合应⽤特性。
8．运筹学的发展趋势是进⼀步依赖于_计算机的应⽤和发展。
9．运筹学解决问题时⾸先要观察待决策问题所处的环境。
10．⽤运筹学分析与解决问题，是⼀个科学决策的过程。
11.运筹学的主要⽬的在于求得⼀个合理运⽤⼈⼒、物⼒和财⼒的最佳⽅案。
12．运筹学中所使⽤的模型是数学模型。
⽤运筹学解决问题的核⼼是建⽴数学模型，并对模型求解。
13⽤运筹学解决问题时，要分析，定议待决策的问题。
14．运筹学的系统特征之⼀是⽤系统的观点研究功能关系。
15.数学模型中，“s·t”表⽰约束。
16．建⽴数学模型时，需要回答的问题有性能的客观量度，可控制因素，不可控因素。
17．运筹学的主要研究对象是各种有组织系统的管理问题及经营活动。
⼆、单选题1.建⽴数学模型时，考虑可以由决策者控制的因素是（ A ）A．销售数量 B．销售价格 C．顾客的需求 D．竞争价格2．我们可以通过（ C ）来验证模型最优解。
A．观察 B．应⽤ C．实验 D．调查3．建⽴运筹学模型的过程不包括（ A ）阶段。
A．观察环境 B．数据分析 C．模型设计 D．模型实施4.建⽴模型的⼀个基本理由是去揭晓那些重要的或有关的（ B ）A数量 B变量 C 约束条件 D ⽬标函数5.模型中要求变量取值（ D ）A可正 B可负 C⾮正 D⾮负6.运筹学研究和解决问题的效果具有（ A ）A 连续性B 整体性C 阶段性D 再⽣性7.运筹学运⽤数学⽅法分析与解决问题，以达到系统的最优⽬标。
数据模型与决策(运筹学)课后习题和案例答案(6)
CHAPTER 7NETWORK OPTIMIZATION PROBLEMS Review Questions7.1-1 A supply node is a node where the net amount of flow generated is a fixed positive number.A demand node is a node where the net amount of flow generated is a fixed negativenumber. A transshipment node is a node where the net amount of flow generated is fixed at zero.7.1-2 The maximum amount of flow allowed through an arc is referred to as the capacity of thatarc.7.1-3 The objective is to minimize the total cost of sending the available supply through thenetwork to satisfy the given demand.7.1-4 The feasible solutions property is necessary. It states that a minimum cost flow problemwill have a feasible solution if and only if the sum of the supplies from its supply nodesequals the sum of the demands at its demand nodes.7.1-5 As long as all its supplies and demands have integer values, any minimum cost flowproblem with feasible solutions is guaranteed to have an optimal solution with integervalues for all its flow quantities.7.1-6 Network simplex method.7.1-7 Applications of minimum cost flow problems include operation of a distribution network,solid waste management, operation of a supply network, coordinating product mixes atplants, and cash flow management.7.1-8 Transportation problems, assignment problems, transshipment problems, maximum flowproblems, and shortest path problems are special types of minimum cost flow problems. 7.2-1 One of the company’s most important distribution centers (Los Angeles) urgently needs anincreased flow of shipments from the company.7.2-2 Auto replacement parts are flowing through the network from the company’s main factoryin Europe to its distribution center in LA.7.2-3 The objective is to maximize the flow of replacement parts from the factory to the LAdistribution center.7.3-1 Rather than minimizing the cost of the flow, the objective is to find a flow plan thatmaximizes the amount flowing through the network from the source to the sink.7.3-2 The source is the node at which all flow through the network originates. The sink is thenode at which all flow through the network terminates. At the source, all arcs point awayfrom the node. At the sink, all arcs point into the node.7.3-3 The amount is measured by either the amount leaving the source or the amount entering thesink.7.3-4 1. Whereas supply nodes have fixed supplies and demand nodes have fixed demands, thesource and sink do not.2. Whereas the number of supply nodes and the number of demand nodes in a minimumcost flow problem may be more than one, there can be only one source and only onesink in a standard maximum flow problem.7.3-5 Applications of maximum flow problems include maximizing the flow through adistribution network, maximizing the flow through a supply network, maximizing the flow of oil through a system of pipelines, maximizing the flow of water through a system ofaqueducts, and maximizing the flow of vehicles through a transportation network.7.4-1 The origin is the fire station and the destination is the farm community.7.4-2 Flow can go in either direction between the nodes connected by links as opposed to onlyone direction with an arc.7.4-3 The origin now is the one supply node, with a supply of one. The destination now is theone demand node, with a demand of one.7.4-4 The length of a link can measure distance, cost, or time.7.4-5 Sarah wants to minimize her total cost of purchasing, operating, and maintaining the carsover her four years of college.7.4-6 When “real travel” through a network can end at more that one node, a dummy destinationneeds to be added so that the network will have just a single destination.7.4-7 Quick’s management must consider trade-offs between time and cost in making its finaldecision.7.5-1 The nodes are given, but the links need to be designed.7.5-2 A state-of-the-art fiber-optic network is being designed.7.5-3 A tree is a network that does not have any paths that begin and end at the same nodewithout backtracking. A spanning tree is a tree that provides a path between every pair of nodes. A minimum spanning tree is the spanning tree that minimizes total cost.7.5-4 The number of links in a spanning tree always is one less than the number of nodes.Furthermore, each node is directly connected by a single link to at least one other node. 7.5-5 To design a network so that there is a path between every pair of nodes at the minimumpossible cost.7.5-6 No, it is not a special type of a minimum cost flow problem.7.5-7 A greedy algorithm will solve a minimum spanning tree problem.17.5-8 Applications of minimum spanning tree problems include design of telecommunicationnetworks, design of a lightly used transportation network, design of a network of high- voltage power lines, design of a network of wiring on electrical equipment, and design of a network of pipelines.Problems7.1a)b)c)1[40] 6 S17 4[-30] D1 [-40] D2 [60] 5 8S2 6[-30] D37.2a)supply nodestransshipment nodesdemand nodesb)[200] P1560 [150]425 [125][0] W1505[150]490 [100]470 [100][-150]RO1[-200]RO2P2 [300]c)510 [175]600 [200][0] W2390 [125]410[150] 440[75]RO3[-150]7.3a)supply nodestransshipment nodesdemand nodesV1W1F1V2V3W2 F21P1W1RO1RO2P2W2RO3[-50] SE3000[20][0]BN5700[40][0]HA[50]BE 4000 6300[40][30] [0][0]NY2000[60]2400[20]3400[10] 4200[80][0]5900[60]5400[40]6800[50]RO[0]BO[0]2500[70]2900[50]b)c)7.4a)LA 3100 NO 6100 LI 3200 ST[-130] [70] [30] [40] [130]1[70]11b)c) The total shipping cost is $2,187,000.7.5a)[0][0] 5900RONY[60] 5400[0] 2900 [50]4200 [80][0] [40] 6800 [50]BO[0] 2500LA 3100 NO 6100 LI 3200 ST [-130][70][30] [40][130]b)c)SEBNHABERONYNY(80) [80] (50) [60](30)[40] ROBO (40)(50) [50] (70)[70]11d)e)f) $1,618,000 + $583,000 = $2,201,000 which is higher than the total in Problem 7.5 ($2,187,000). 7.6LA(70) NO[50](30)LI (30) ST[70][30] [40]There are only two arcs into LA, with a combined capacity of 150 (80 + 70). Because ofthis bottleneck, it is not possible to ship any more than 150 from ST to LA. Since 150 actually are being shipped in this solution, it must be optimal. 7.7[-50] SE3000 [20] [0] BN 5700 [40][0] HA[50] BE4000 6300[40][0] NY2000 [60] 2400 [20][30] [0]5900RO [60]17.8 a) SourcesTransshipment Nodes Sinkb)7.9 a)AKR1[75]A [60]R2[65] [40][50][60] [45]D [120] [70]B[55]E[190]T [45][80] [70][70]R3CF[130][90]SE PT KC SL ATCHTXNOMES S F F CAb)Oil Fields Refineries Distribution CentersTXNOPTCACHATAKSEKCME c)SLSFTX[11][7] NO[5][9] PT[8] [2][5] CA [4] [7] [8] [7] [4] [6][8] CH [7][5][9] [4] ATAK [3][6][6][12] SE KC[8][9][4][8] [7] [12] [11]MESL [9]SF[15][7]d)3Shortest path: Fire Station – C – E – F – Farming Community 7.11 a)A70D40 60O60 5010 B 20 C5540 10 T50E801c)Shortest route: Origin – A – B – D – Destinationd)Yese)Yes7.12a)31,00018,000 21,00001238,000 10,000 12,000b)17.13a) Times play the role of distances.B 2 2 G5ACE 1 31 1b)7.14D F1. C---D: Cost = 14.E---G: Cost = 5E---F: Cost = 1 *choose arbitrarilyD---A: Cost = 4 2.E---G: Cost = 5 E---B: Cost = 7 E---B: Cost = 7 F---G: Cost = 7 E---C: Cost = 4 C---A: Cost = 5F---G: Cost = 7C---B: Cost = 2 *lowestF---C: Cost = 3 *lowest5.E---G: Cost = 5 F---D: Cost = 4 D---A: Cost = 43. E---G: Cost = 5 B---A: Cost = 2 *lowestE---B: Cost = 7 F---G: Cost = 7 F---G: Cost = 7 C---A: Cost = 5F---D: Cost = 46.E---G: Cost = 5 *lowestC---D: Cost = 1 *lowestF---G: Cost = 7C---A: Cost = 5C---B: Cost = 2Total = $14 million7.151. B---C: Cost = 1 *lowest 4. B---E: Cost = 72. B---A: Cost = 4 C---F: Cost = 4 *lowestB---E: Cost = 7 C---E: Cost = 5C---A: Cost = 6 D---F: Cost = 5C---D: Cost = 2 *lowest 5. B---E: Cost = 7C---F: Cost = 4 C---E: Cost = 5C---E: Cost = 5 F---E: Cost = 1 *lowest3. B---A: Cost = 4 *lowest F---G: Cost = 8B---E: Cost = 7 6. E---G: Cost = 6 *lowestC---A: Cost = 6 F---G: Cost = 8C---F: Cost = 4C---E: Cost = 5D---A: Cost = 5 Total = $18,000D---F: Cost = 57.16B 34 2E HA D 2 G I K3C F 12J34B41E6A C41G2 FD1. F---G: Cost = 1 *lowest 6. D---A: Cost = 62. F---C: Cost = 6 D---B: Cost = 5F---D: Cost = 5 D---C: Cost = 4F---I: Cost = 2 *lowest E---B: Cost = 3 *lowestF---J: Cost = 5 F---C: Cost = 6G---D: Cost = 2 F---J: Cost = 5G---E: Cost = 2 H---K: Cost = 7G---H: Cost = 2 I---K: Cost = 8G---I: Cost = 5 I---J: Cost = 33. F---C: Cost = 6 7. B---A: Cost = 4F---D: Cost = 5 D---A: Cost = 6F---J: Cost = 5 D---C: Cost = 4G---D: Cost = 2 *lowest F---C: Cost = 6G---E: Cost = 2 F---J: Cost = 5G---H: Cost = 2 H---K: Cost = 7I---H: Cost = 2 I---K: Cost = 8I---K: Cost = 8 I---J: Cost = 3 *lowestI---J: Cost = 3 8. B---A: Cost = 4 *lowest4. D---A: Cost = 6 D---A: Cost = 6D---B: Cost = 5 D---C: Cost = 4D---E: Cost = 2 *lowest F---C: Cost = 6D---C: Cost = 4 H---K: Cost = 7F---C: Cost = 6 I---K: Cost = 8F---J: Cost = 5 J---K: Cost = 4G---E: Cost = 2 9. A---C: Cost = 3 *lowestG---H: Cost = 2 D---C: Cost = 4I---H: Cost = 2 F---C: Cost = 6I---K: Cost = 8 H---K: Cost = 7I---J: Cost = 3 I---K: Cost = 85. D---A: Cost = 6 J---K: Cost = 4D---B: Cost = 5 10. H---K: Cost = 7D---C: Cost = 4 I---K: Cost = 8E---B: Cost = 3 J---K: Cost = 4 *lowestE---H: Cost = 4F---C: Cost = 6F---J: Cost = 5G---H: Cost = 2 *lowest Total = $26 millionI---H: Cost = 2I---K: Cost = 8I---J: Cost = 37.17a) The company wants a path between each pair of nodes (groves) that minimizes cost(length of road).b)7---8 : Distance = 0.57---6 : Distance = 0.66---5 : Distance = 0.95---1 : Distance = 0.75---4 : Distance = 0.78---3 : Distance = 1.03---2 : Distance = 0.9Total = 5.3 miles7.18a) The bank wants a path between each pair of nodes (offices) that minimizes cost(distance).b) B1---B5 : Distance = 50B5---B3 : Distance = 80B1---B2 : Distance = 100B2---M : Distance = 70B2---B4 : Distance = 120Total = 420 milesHamburgBostonRotterdamSt. PetersburgNapoliMoscowA IRFIELD SLondonJacksonvilleBerlin RostovIstanbulCases7.1a) The network showing the different routes troops and supplies may follow to reach the Russian Federation appears below.PORTSb)The President is only concerned about how to most quickly move troops and suppliesfrom the United States to the three strategic Russian cities. Obviously, the best way to achieve this goal is to find the fastest connection between the US and the three cities.We therefore need to find the shortest path between the US cities and each of the three Russian cities.The President only cares about the time it takes to get the troops and supplies to Russia.It does not matter how great a distance the troops and supplies cover. Therefore we define the arc length between two nodes in the network to be the time it takes to travel between the respective cities. For example, the distance between Boston and London equals 6,200 km. The mode of transportation between the cities is a Starlifter traveling at a speed of 400 miles per hour * 1.609 km per mile = 643.6 km per hour. The time is takes to bring troops and supplies from Boston to London equals 6,200 km / 643.6 km per hour = 9.6333 hours. Using this approach we can compute the time of travel along all arcs in the network.By simple inspection and common sense it is apparent that the fastest transportation involves using only airplanes. We therefore can restrict ourselves to only those arcs in the network where the mode of transportation is air travel. We can omit the three port cities and all arcs entering and leaving these nodes.The following six spreadsheets find the shortest path between each US city (Boston and Jacksonville) and each Russian city (St. Petersburg, Moscow, and Rostov).The spreadsheets contain the following formulas:Comparing all six solutions we see that the shortest path from the US to Saint Petersburg is Boston → London → Saint Petersburg with a total travel time of 12.71 hours. The shortest path from the US to Moscow is Boston → London → Moscow with a total travel time of 13.21 hours. The shortest path from the US to Rostov is Boston →Berlin → Rostov with a total travel time of 13.95 hours. The following network diagram highlights these shortest paths.-1c)The President must satisfy each Russian city’s military requirements at minimum cost.Therefore, this problem can be solved as a minimum-cost network flow problem. The two nodes representing US cities are supply nodes with a supply of 500 each (wemeasure all weights in 1000 tons). The three nodes representing Saint Petersburg, Moscow, and Rostov are demand nodes with demands of –320, -440, and –240,respectively. All nodes representing European airfields and ports are transshipment nodes. We measure the flow along the arcs in 1000 tons. For some arcs, capacityconstraints are given. All arcs from the European ports into Saint Petersburg have zero capacity. All truck routes from the European ports into Rostov have a transportation limit of 2,500*16 = 40,000 tons. Since we measure the arc flows in 1000 tons, the corresponding arc capacities equal 40. An analogous computation yields arc capacities of 30 for both the arcs connecting the nodes London and Berlin to Rostov. For all other nodes we determine natural arc capacities based on the supplies and demands at the nodes. We define the unit costs along the arcs in the network in $1000 per 1000 tons (or, equivalently, $/ton). For example, the cost of transporting 1 ton of material from Boston to Hamburg equals $30,000 / 240 = $125, so the costs of transporting 1000 tons from Boston to Hamburg equals $125,000.The objective is to satisfy all demands in the network at minimum cost. The following spreadsheet shows the entire linear programming model.HamburgBoston Rotterdam St.Petersburg+500-320Napoli Moscow A IRF IELDSLondon -440Jacksonville Berlin Rostov+500-240Istanbul The total cost of the operation equals $412.867 million. The entire supply for SaintPetersburg is supplied from Jacksonville via London. The entire supply for Moscow is supplied from Boston via Hamburg. Of the 240 (= 240,000 tons) demanded by Rostov, 60 are shipped from Boston via Istanbul, 150 are shipped from Jacksonville viaIstanbul, and 30 are shipped from Jacksonville via London. The paths used to shipsupplies to Saint Petersburg, Moscow, and Rostov are highlighted on the followingnetwork diagram.PORTSd)Now the President wants to maximize the amount of cargo transported from the US tothe Russian cities. In other words, the President wants to maximize the flow from the two US cities to the three Russian cities. All the nodes representing the European ports and airfields are once again transshipment nodes. The flow along an arc is againmeasured in thousands of tons. The new restrictions can be transformed into arccapacities using the same approach that was used in part (c). The objective is now to maximize the combined flow into the three Russian cities.The linear programming spreadsheet model describing the maximum flow problem appears as follows.The spreadsheet shows all the amounts that are shipped between the various cities. The total supply for Saint Petersburg, Moscow, and Rostov equals 225,000 tons, 104,800 tons, and 192,400 tons, respectively. The following network diagram highlights the paths used to ship supplies between the US and the Russian Federation.PORTSHamburgBoston Rotterdam St.Petersburg+282.2 -225NapoliMoscowAIRFIELDS-104.8LondonJacksonvilleBerlin Rostov +240 -192.4Istanbule)The creation of the new communications network is a minimum spanning tree problem.As usual, a greedy algorithm solves this type of problem.Arcs are added to the network in the following order (one of several optimal solutions):Rostov - Orenburg 120Ufa - Orenburg 75Saratov - Orenburg 95Saratov - Samara 100Samara - Kazan 95Ufa – Yekaterinburg 125Perm – Yekaterinburg 857.2a) There are three supply nodes – the Yen node, the Rupiah node, and the Ringgit node.There is one demand node – the US$ node. Below, we draw the network originatingfrom only the Yen supply node to illustrate the overall design of the network. In thisnetwork, we exclude both the Rupiah and Ringgit nodes for simplicity.b)Since all transaction limits are given in the equivalent of $1000 we define the flowvariables as the amount in thousands of dollars that Jake converts from one currencyinto another one. His total holdings in Yen, Rupiah, and Ringgit are equivalent to $9.6million, $1.68 million, and $5.6 million, respectively (as calculated in cells I16:K18 inthe spreadsheet). So, the supplies at the supply nodes Yen, Rupiah, and Ringgit are -$9.6 million, -$1.68 million, and -$5.6 million, respectively. The demand at the onlydemand node US$ equals $16.88 million (the sum of the outflows from the sourcenodes). The transaction limits are capacity constraints for all arcs leaving from thenodes Yen, Rupiah, and Ringgit. The unit cost for every arc is given by the transactioncost for the currency conversion.Jake should convert the equivalent of $2 million from Yen to each US$, Can$, Euro, and Pound. He should convert $1.6 million from Yen to Peso. Moreover, he should convert the equivalent of $200,000 from Rupiah to each US$, Can$, and Peso, $1 million from Rupiah to Euro, and $80,000 from Rupiah to Pound. Furthermore, Jake should convert the equivalent of $1.1 million from Ringgit to US$, $2.5 million from Ringgit to Euro, and $1 million from Ringgit to each Pound and Peso. Finally, he should convert all the money he converted into Can$, Euro, Pound, and Peso directly into US$. Specifically, he needs to convert into US$ the equivalent of $2.2 million, $5.5 million, $3.08 million, and $2.8 million Can$, Euro, Pound, and Peso, respectively. Assuming Jake pays for the total transaction costs of $83,380 directly from his American bank accounts he will have $16,880,000 dollars to invest in the US.c)We eliminate all capacity restrictions on the arcs.Jake should convert the entire holdings in Japan from Yen into Pounds and then into US$, the entire holdings in Indonesia from Rupiah into Can$ and then into US$, and the entire holdings in Malaysia from Ringgit into Euro and then into US$. Without the capacity limits the transaction costs are reduced to $67,480.d)We multiply all unit cost for Rupiah by 6.The optimal routing for the money doesn't change, but the total transaction costs are now increased to $92,680.e)In the described crisis situation the currency exchange rates might change every minute.Jake should carefully check the exchange rates again when he performs thetransactions.The European economies might be more insulated from the Asian financial collapse than the US economy. To impress his boss Jake might want to explore other investment opportunities in safer European economies that provide higher rates of return than US bonds.。
数据模型与决策课程学习大作业.doc
数据模型与决策课程大作业以我国汽油消费量为因变量，乘用车销量、城镇化率和90#汽油吨价与城镇居民人均可支配收入的比值为自变量时行回归（数据为年度时间序列数据）。
试根据得到部分输出结果，回答下列问题：1）“模型汇总表”中的R方和标准估计的误差是多少？2）写出此回归分析所对应的方程；3）将三个自变量对汽油消费量的影响程度进行说明；4）对回归分析结果进行分析和评价，指出其中存在的问题。
1）“模型汇总表”中的R方和标准估计的误差是多少？答案：R方为0.993^2=0.986 ；标准估计的误差为120910.147^（0.5）=347.722）写出此回归分析所对应的方程；答案：假设汽油消费量为Y，乘用车销量为a，城镇化率为b，90#汽油吨价/城镇居民人均可支配收入为c,则回归方程为：Y=240.534+0.00s027a+8649.895b-198.692c3）将三个自变量对汽油消费量的影响程度进行说明；乘用车销量对汽油消费量相关系数只有0.00027，数值太小，几乎没有影响，但是城镇化率对汽油消费量相关系数是8649.895，具有明显正相关，当城镇化率每提高1，汽油消费量增加8649.895。
乘用90#汽油吨价/城镇居民人均可支配收入相关系数为-198.692，呈明显负相关，即乘用90#汽油吨价/城镇居民人均可支配收入每增加1个单位，汽油消费量降低198.692个单位。
a, b, c三个自变量的sig 值为0.000、0.000、0.009，在显著性水平0.01情形下，乘用车消费量对汽油消费量的影响显著为正。
（4）对回归分析结果进行分析和评价，指出其中存在的问题。
在学习完本课程之后，我们可以统计方法为特征的不确定性决策、以运筹方法为特征的策略的基本原理和一般方法为基础，结合抽样、参数估计、假设分析、回归分析等知识对我国汽油消费量影响因素进行了模拟回归，并运用软件计算出回归结果，故根据回归结果，对具体回归方程，回归准确性，自变量影响展开分析。
(完整版)30447数据模型与决策2014年07月【答案】
1-5、ACBAD 6-10、BBACD 11、数学模型 12、双相抽样 13、4.8814、一个测量原点，也叫绝对零点 15、熵16、置信度或置信水平 17、方差分析 18、自变量 19、循环变动 20、波动问题21、数据质量检查的抽样方法：在一次调查之后，紧接着再从这些被调查单位中抽取一定数量的单位组成样本，重新调查登记，最后将两者的结果进行对比，以检查先前调查数据的质量并进行适当的调整。
22、控制图：它是运用统计方法确定管理界限，并用于管理监控的一种图标。
23、中位数：把观察值按从小到大的顺序排列位置居中的数叫做中位数。
24、变异系数：是把算术平均数与标准差联系起来的一个测度，它的公式为100%Ss C x25、折中准则：小中求大准则过于悲观，大中求大准则过于乐观。
折中准则就是小中求大和大众求大准则之间进行平衡，以希望决策更符合现实。
通过对行样本频率能进行列类别间的比较，志愿活动是为了体现个人价值的男性比超过女性比。
2292644.8232868.220.4269133743289614.44468.22通过计算说明救济水平与解雇率之间有一定的相关性，但不是很高。
28、20001999199819972001169.2144.5126.1103.5135.82544x x x x x 2000199919981997200194.7116.0137.9178.3131.72544x x x x x 200019991998199********.6141.2159.2152.9142.97544x x x x x 20001999199819972001109.3131.9146.8166.0138.544x x x x x29、1(200.015)(200.015)2022u T Tˆ20x ，可以直接利用公式进行计算1(200.015)(200.015)16660.005u pST T T C30、解：设每种型号的拖拉机各购买1234,,,x x x x 台。
数据模型与决策 习题答案
数据模型与决策习题答案数据模型与决策习题答案在当今信息时代，数据的价值越来越受到重视。
数据模型作为一种描述和组织数据的方式，对于决策过程起着重要的作用。
本文将通过解答一些与数据模型和决策相关的习题，来探讨数据模型在决策中的应用和意义。
1. 什么是数据模型？为什么在决策过程中需要使用数据模型？数据模型是对现实世界进行抽象和描述的一种方式。
它通过定义实体、属性和关系的方式，将现实世界中的事物转化为计算机可以处理的形式。
数据模型可以帮助我们更好地理解和组织数据，为决策提供支持。
在决策过程中，数据模型的使用具有以下几个重要的作用：1) 数据模型可以帮助我们对现实世界进行建模和描述，将复杂的现实问题转化为可计算的形式，从而更好地理解问题的本质。
2) 数据模型可以帮助我们组织和管理大量的数据，使得数据更易于存储、检索和分析，为决策提供必要的信息支持。
3) 数据模型可以帮助我们对不同的决策方案进行评估和比较，通过模拟和预测的方式，帮助我们选择最佳的决策方案。
2. 数据模型的种类有哪些？请简要介绍其中的几种。
常见的数据模型包括层次模型、网状模型、关系模型和面向对象模型等。
层次模型是最早的数据模型之一，它将数据组织成一种树状结构，其中每个节点代表一个实体，每个节点之间通过父子关系连接。
层次模型的优点是结构简单，易于理解和实现，但缺点是不适合处理复杂的关系和多对多的关联。
网状模型是层次模型的扩展，它允许多个父节点指向同一个子节点，从而解决了层次模型不适合处理多对多关联的问题。
但网状模型的缺点是结构复杂，不易理解和维护。
关系模型是目前应用最广泛的数据模型，它将数据组织成一张二维表格，其中每一行代表一个实体，每一列代表一个属性。
关系模型通过定义实体间的关系和约束，实现了数据的灵活查询和操作。
面向对象模型是一种基于对象的数据模型，它将数据组织成一组对象，每个对象包含了数据和对数据的操作。
面向对象模型适用于处理复杂的关系和行为，但在实际应用中较为复杂和庞大。
数据模型与决策课
数据模型与决策课程大作业数据模型与决策课程大作业以我国汽油消费量为因变量，乘用车销量、城镇化率和90#汽油吨价与城镇居民人均可支配收入的比值为自变量时行回归（数据为年度时间序列数据）。
试根据得到部分输出结果，回答下列问题：1）“模型汇总表”中的R方和标准估计的误差是多少？2）写出此回归分析所对应的方程；3）将三个自变量对汽油消费量的影响程度进行说明；4）对回归分析结果进行分析和评价，指出其中存在的问题。
1）“模型汇总表”中的R方和标准估计的误差是多少？答案：R方为0.993^2=0.986 ；标准估计的误差为120910.147^（0.5）=347.722）写出此回归分析所对应的方程；答案：假设汽油消费量为Y，乘用车销量为a，城镇化率为b，90#汽油吨价/城镇居民人均可支配收入为c,则回归方程为：Y=240.534+0.00s027a+8649.895b-198.692c3）将三个自变量对汽油消费量的影响程度进行说明；乘用车销量对汽油消费量相关系数只有0.00027，数值太小，几乎没有影响，但是城镇化率对汽油消费量相关系数是8649.895，具有明显正相关，当城镇化率每提高1，汽油消费量增加8649.895。
乘用90#汽油吨价/城镇居民人均可支配收入相关系数为-198.692，呈明显负相关，即乘用90#汽油吨价/城镇居民人均可支配收入每增加1个单位，汽油消费量降低198.692个单位。
a, b, c三个自变量的sig 值为0.000、0.000、0.009，在显著性水平0.01情形下，乘用车消费量对汽油消费量的影响显著为正。
（4）对回归分析结果进行分析和评价，指出其中存在的问题。
在学习完本课程之后，我们可以统计方法为特征的不确定性决策、以运筹方法为特征的策略的基本原理和一般方法为基础，结合抽样、参数估计、假设分析、回归分析等知识对我国汽油消费量影响因素进行了模拟回归，并运用软件计算出回归结果，故根据回归结果，对具体回归方程，回归准确性，自变量影响展开分析。
数据模型与决策试题及参考答案
《数据模型与决策》复习（附参考答案）2018.9一、填空题（五题共15分）1.已知成年男子的身高服从正态分布N（167.48,6.092），随机调查100位成年男子的身高，那么，这100位男子身高的平均数服从的分布是①。
解：N（167.48,0.609）考查知识点：已知总体服从正态分布，求样本均值的分布。
2.某高校想了解大学生每个月的消费情况，随机抽取了100名大学生，算得平均月消费额为1488元，标准差是2240元。
根据正态分布的“68-95-99”法则，该高校大学生每个月的消费额的95%估计区间为②。
解：[1040,1936]考查知识点：区间估计的求法。
正态总体均值的区间估计是[X-Z上,X + Z与] 1-a n'n1-a nn 其中X是样本平均数，s是样本的标准差，n是样本数。
详解：直接带公式得：区间估计是— s _ s2240 2240[X—Z -=, X + Z ，]= [1488 —2^^,1488 + 2^^] 山nn山.nn x100 * 100=[1040,1936]3.从遗传规律看，一个产妇生男生女的概率是一样的，都是50%，但也有个人的特殊情况。
假设某人前一胎是女孩，那么她的下一胎也是女孩的概率为0.55；如果某人前一胎是男孩，那么她的下一胎还是男孩的概率为0.48。
已知小李第一胎是女孩，那么她的第三胎生男孩的概率是③。
解p=0.4653考查知识点：离散概率计算方法。
详解：假设B1二第1胎生男孩，B2二第2胎生男孩，B3二第3胎生男孩G1二第1胎生女孩，G2=第2胎生女孩，G3=第3胎生女孩P（B3）二P（B3B2）+P（B3G2）（直观解释是：第二胎生男孩的情况下第三胎生男孩，第二胎生女孩的情况下第三胎生男孩，两个概率之和为P（B3））= P(B3|B2)P(B2)+P(B3|G2)P(G2)=0.48 义(1-0.55) + (1-0.55)义 0.55=0.46534.调查发现，一个刚参加工作的MBA毕业生在顶级管理咨询公司的初始年薪可以用均值为9万美元和标准差是2万美元的正态分布来表示，那么一个这样的毕业生初始年薪超过9万美元的概率是④。
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数据模型与决策课程大作业
以我国汽油消费量为因变量，乘用车销量、城镇化率和90#汽油吨价与城镇居民人均可支配收入的比值为自变量时行回归（数据为年度时间序列数据）。
试根据得到部分输出结果，回答下列问题：1）“模型汇总表”中的R方和标准估计的误差是多少
2）写出此回归分析所对应的方程；
3）将三个自变量对汽油消费量的影响程度进行说明；
4）对回归分析结果进行分析和评价，指出其中存在的问题。
1）“模型汇总表”中的R方和标准估计的误差是多少
答案：R方为^2= ；标准估计的误差为^（）=
2）写出此回归分析所对应的方程；
答案：假设汽油消费量为Y，乘用车销量为a，城镇化率为b，90#汽油吨价/城镇居民人均可支配收入为c,则回归方程为：
Y=++）将三个自变量对汽油消费量的影响程度进行说明；
乘用车销量对汽油消费量相关系数只有，数值太小，几乎没有影响，但是城镇化率对汽油消费量相关系数是，具有明显正相关，当城镇化率每提高1，汽油消费量增加。
乘用90#汽油吨价/城镇居民人均可支配收入相关系数为，呈明显负相关，即乘用90#汽油吨价/城镇居民人均可支配收入每增加1个单位，汽油消费量降低个单位。
a, b, c三个自变量的sig值为、、，在显着性水平情形下，乘用车消费量对
汽油消费量的影响显着为正。
（4）对回归分析结果进行分析和评价，指出其中存在的问题。
在学习完本课程之后，我们可以统计方法为特征的不确定性决策、以运筹方法为特征的策略的基本原理和一般方法为基础，结合抽样、参数估计、假设分析、回归分析等知识对我国汽油消费量影响因素进行了模拟回归，并运用软件计算出回归结果，故根据回归结果，对具体回归方程，回归准确性，自变量影响展开分析。
Anova表中，sig值是t统计量对应的概率值，所以t和sig两者是等效的，sig要小于给定的显着性水平，越接近于0越好。
F是检验方程显着性的统计量，是平均的回归平方和平均剩余平方和之比，越大越好。
在图表中，回归模型统计值F=，p值为，因此证明回归模型有统计学意义，表现回归极显着。
即因变量与三个自变量之间存在线性关系。
系数表中，除了常数项系数显着性水平大于，不影响，其它项系数都是，小于，即每个回归系数均具有意义。
当然，这其中也存在一定的问题：
在模型设计中，乘用车销量为、城镇化率为、90#汽油吨价/城镇居民人均可支配收入为三个自变量的单位均不同，因此会造成自变量前面的回归系数不具有准确的宏观意义，因此需要对模型进行实现标准化，也就是引入β系数，消除偏回归系数带来的数量单位影响。
根据共线性统计量中的变量的容差t和方差膨胀因子（VIF），自变量间存在共性问题，容差和膨胀因子为倒数关系，容差越小，膨胀因子越大，尤其是城镇化率VIF为，说明共线性明显，可能原因是由于样本容量太小，也可能是城镇化之后乘用车销售量和、90#汽油吨价/城镇居民人均可支配收入本身就具有相关性。
缺乏模型异方差检验。
在多元回归模型中，由于数据质量原因、模型设定原因，异方差的存在会使回归系数估计结果误差较多，所以在建立模型分析的过程红要对异方差进行检验。
数据模型与决策使我们学会使用科学的分析和决策，对经营管理活动实现合理化、精细化、科学化，从而避免了盲目的生产活动。
通过数据预测、假设检验、公式、分析、验证等一系列的步骤，将数据结果逐一展现。
为我们的学习和工作提供了一些非常有用、便捷的，处理问题的方法。
附表：t分布表：
单尾检验的显着水平
df
双尾检验的显着水平
3 4 5 6 7 8 9 10 11 12 13。