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Statistics Chap12, Cases

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Chapter 12 Simple Linear Regression Case Problem 1: Measuring Stock Market Risk a. Selected descriptive statistics follow: Variable N Mean StDev Minimum Median Maximum Microsoft 36 0.00503 0.04537 -0.08201 0.00400 0.08883 Exxon Mobil 36 0.01664 0.05534 -0.11646 0.01279 0.23217 Caterpillar 36 0.03010 0.06860 -0.10060 0.04080 0.21850 Johnson & Johnson 36 0.00530 0.03487 -0.05917 -0.00148 0.10334 McDonald’s 36 0.02450 0.06810 -0.11440 0.03700 0.18260 Sandisk 36 0.06930 0.19540 -0.28330 0.07410 0.50170 Qualcomm 36 0.02840 0.08620 -0.12170 0.03870 0.21060 Procter & Gamble 36 0.01059 …show more content…

PERCENT FATAL Fit Stdev.Fit Residual St.Resid 15 10.0 0.0390 1.2731 0.1126 -1.2341 -2.13R 23 8.0 2.1900 0.6990 0.1548 1.4910 2.62R R denotes an obs. with a large st. resid. There is a significant relationship between the two variables. Two observations are identified as having a large standardized residual and should be treated as possible outliers; the following standardized residual plot does not indicate any other problems with the residuals. [pic] Conclusion: It appears that the number of fatal accidents per 1000 licenses is linearly related to the percentage of licensed drivers under the age of 21; that is, the higher the percentage of drivers under 21, the larger the number of total accidents. Case Problem 3: Alumni Giving 1. Numerical and graphical summaries of the data follow. Variable N Mean Median TrMean StDev SE Mean Under 20 48 55.73 59.50 56.02 13.19 1.90 S/FRatio 48 11.542 10.500

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