Power 16ProjectsLogisticsAssignmentsPowerPoint Presentations: Member 4Executive Summary and Technical AppendixSlide 7Technical AppendixTechnical Appendix (Cont.)Slide ShowChallenger DisasterSlide 12Launches Before ChallengerSlide 14Slide 15Slide 16Exploratory AnalysisSlide 18Slide 19Slide 20OutlineAnova and Regression: One-WaySlide 23Anova and Regression: One-Way Alternative SpecificationSlide 25ANOVA and Regression: Two-Way Series of Regressions; Compare to Table 11, Lecture 15Slide 27ANOVA and Regression: Two-Way Series of RegressionsNonparametric Statistics3 Nonparametric TechniquesWilcoxon Rank Sum Test for Independent SamplesRating schemeSlide 33Rank the 30 RatingsSlide 35Slide 36Slide 37Rank Sum, TSlide 391Power 162Projects3Logistics•Put power point slide show on a high density floppy disk for a WINTEL machine.•Email [email protected] the slide-show as a PowerPoint attachment4Assignments• 1. Project choice• 2. Data Retrieval•3. Statistical Analysis•4. PowerPoint Presentation•5. Executive Summary•6. Technical AppendixPower_125PowerPoint Presentations: Member 4•1. Introduction: Members 1 ,2 , 3–What–Why–How•2. Executive Summary: Member 5•3. Exploratory Data Analysis: Member 3•4. Descriptive Statistics: Member 3•5. Statistical Analysis: Member 3•6. Conclusions: Members 3 & 5• 7. Technical Appendix: Table of Contents, Member 66Executive Summary and Technical Appendix7I. Your report should have an executive summary of one to oneand a half pages that summarizes your findings in words for a non-technical reader. It should explain the problem being examinedfrom an economic perspective, i.e. it should motivate interest in theissue on the part of the reader. Your report should explain how youare investigating the issue, in simple language. It should explainwhy you are approaching the problem in this particular fashion.Your executive report should explain the economic importance ofyour findings.The technical details of your findings you can attach as anappendix.8Technical Appendix•Table of Contents•Spreadsheet of data used and sources or if extensive, a subsample of the data•Descriptive Statistics and Histograms for the variables in the study•If time series data, a plot of each variable against time•If relevant, plot of the dependent Vs. each of the explanatory variables9Technical Appendix (Cont.)•Statistical Results, for example regression•Plot of the actual, fitted and error and other diagnostics•Brief summary of the conclusions, meanings drawn from the exploratory, descriptive, and statistical analysis.10Slide Show•Challenger disaster11Challenger Disaster•Failure of O-rings that sealed grooves on the booster rockets•Was there any relationship between o-ring failure and temperature?•Engineers knew that the rubber o-rings hardened and were less flexible at low temperatures•But was ther launch dat that showed a problem12Challenger Disaster•What: Was ther a relationship between launch temperature and o-ring failure prior to the Challenger disaster?•Why: Should the launch have proceeded?•How: Analyze the relationship between launch temperature and o-ring failure13Launches Before Challenger•Data–number of o-rings that failed–launch temperature14o-rings temperature3 531 571 581 630 660 670 670 670 680 691 7015o-rings temperature1 700 700 700 720 732 750 750 760 760 780 7916o-rings temperature0 800 8117Exploratory Analysis•Launches where there was a problem181 581 571 701 631 702 753 53Orings temperature0.51.01.52.02.53.03.550 55 60 65 70 75 80TEMPORINGS0123450 60 70 80 90TEMPORINGS21Outline•ANOVA and Regression•Non-Parametric Statistics•Goodman Log-Linear Model22Anova and Regression: One-Way•Salesaj = c(1)*convenience+c(2)*quality+c(3)*price+ e•E[salesaj/(convenience=1, quality=0, price=0)] =c(1) = mean for city(1)–c(1) = mean for city(1) (convenience)–c(2) = mean for city(2) (quality)–c(3) = mean for city(3) (price)–Test the null hypothesis that the means are equal using a Wald test: c(1) = c(2) = c(3)Table 5: One-Way ANOVA Estimated Using RegressionDependent Variable: SALESAJMethod: Least SquaresSample: 1 60Included observations: 60Variable Coefficient Std. Error t-Statistic Prob.CONVENIENCE 577.5500 21.08844 27.38704 0.0000QUALITY 653.0000 21.08844 30.96483 0.0000PRICE 608.6500 21.08844 28.86178 0.0000R-squared 0.101882 Mean dependent var 613.0667Adjusted R-squared0.070370 S.D. dependent var 97.81474S.E. of regression 94.31038 Akaike info criterion 11.97977Sum squaredresid506983.5 Schwarz criterion 12.08448Log likelihood -356.3930 F-statistic 3.233041Durbin-Watsonstat1.525930 Prob(F-statistic) 0.046773One-Way ANOVA and RegressionRegression Coefficients are the City Means; F statistic24Anova and Regression: One-WayAlternative Specification•Salesaj = c(1) + c(2)*convenience+c(3)*quality+e•E[Salesaj/(convenience=0, quality=0)] = c(1) = mean for city(3) (price, the omitted one)•E[Salesaj/(convenience=1, quality=0)] = c(1) + c(2) = mean for city(1) (convenience)–c(1) = mean for city(3), the omitted city–c(2) = mean for city(1) minus mean for city(3)–Test that the mean for city(1) = mean for city(3)–Using the t-statistic for c(2)25Anova and Regression: One-WayAlternative Specification•Salesaj = c(1) + c(2)*convenience+c(3)*price+e•E[Salesaj/(convenience=0, price=0)] = c(1) = mean for city(2) (quality, the omitted one)•E[Salesaj/(convenience=1, price=0)] = c(1) + c(2) = mean for city(1) (convenience)–c(1) = mean for city(2), the omitted city–c(2) = mean for city(1) minus mean for city(2)–Test that the mean for city(1) = mean for city(2)–Using the t-statistic for c(2)26ANOVA and Regression: Two-WaySeries of Regressions; Compare to Table 11, Lecture 15•Salesaj = c(1) + c(2)*convenience + c(3)* quality + c(4)*television + c(5)*convenience*television + c(6)*quality*television + e, SSR=501,136.7•Salesaj = c(1) + c(2)*convenience + c(3)* quality + c(4)*television + e, SSR=502,746.3•Test for interaction effect: F2, 54 = [(502746.3-501136.7)/2]/(501136.7/54) = (1609.6/2)/9280.3 = 0.09Table 11: 2-Way ANOVA of Apple Juice SalesSource of Variation Sum of Squares Degrees ofFreedomMean SquareExplained(betweentreatments)ESS =Strategy ESS(Strat) = 98838.6 (a-1) = 2 49419.3Medium ESS(Med) = 13172.0 (b-1) = 1 13172.0Interaction ESS(I) = 1609.6 (a-1)(b-1) = 2 804.8Unexplained(withintreatments)USS = 501136.7 (n-ab) = 60 – 6= 549280.3Total TSS =
View Full Document
Unlocking...