1. 2. 3. 4. 5. PRONTO-15 TF Questions Based on the t statistic, we can reject the null hypothesis that the mean of total time is 25 minutes or less when testing at alpha=.01 [from Data=Pronto1]. A. True B. False Based on the Kolmogorov-Smirnov D statistics, we would reject (at a=.01) the null hypothesis that the distribution of total times is normal [from Data=Pronto1]. A. True B. False The probability of rejecting the null hypothesis of a normal distribution increases when extreme outliers are eliminated [from data=Pronto1]. A. True B. False The number of observations where total time is at least a minute over the 'guaranteed 29' minutes is 30 [from Data=Pronto1]. A. True B. False On week-ends (Fri Sat), average wait time is higher at 5:00pm than for other hours of the day. [GLM model from Data=Pronto2] A. True B. False 6. Average 'travel' time is higher at 5:00 pm than the other hours of the day on week-end days (Fri-Sat) [GLM model from Data=Pronto2]. 7. 8. 9. A. True B. False Based on SAS output for a General Linear Model (Proc GLM), there is a significant difference (at a=.01) in mean 'wait' time between the five-pm hour and the other hours of the day [GLM model from Data=Pronto2]. A. True B. False In the sample, there are exactly twice as many observations during weekdays as there are for the weekend days (Fri. Sat) [GLM model from Data=Pronto2]. A. True B. False On average, total time is more than two minutes more for Friday-Saturday than for the other days of the week [Regression Model from Data=Pronto3]. A. True B. False 10. On average, total time is more than two minutes more for 5:00pm than for the other hours of the day [Regression Model from Data=Pronto3]. 11. 12. 13. 14. A. True B. False Each additional mile adds more than two minutes to total time [Regression Model from Data=Pronto3]. A. True B. False The larger the number of observations, the larger will be the difference between the adjusted R-Square and R-Square [Regression Model from Data=Pronto3]. A. True B. False The average amount of variation explained is over 50 times the average amount unexplained [Regression Model from Data=Pronto3]. A. True B. False All three explanatory variables are significant at a=.05 [Regression Model from Data=Pronto3]. A. True B. False 15. The parameter estimate for 5:00pm is more than four standard errors from its hypothesized value [B=0] [Regression Model from Data=Pronto3]. A. True B. False PRONTO - SAS OUTPUT TTEST Procedure - From Pronto1 Ho: 25 mins. Ha: > 25 mins. Variable: Total N Mean Std Dev Std Err Min Max 240 25.32 3.93 0.2534 16.90 46.00 DF t Value Pr t 239 1.26 0.1036 Test Tests for Normality Statistic p Value Kolmogorov-Smirnov D 0.11 Pr>D F Model 3 408.28 136.09 15.11 F 1 324.77 324.77 36.05 The REG Procedure - From Pronto3 with extreme values deleted Dependent Variable: Total Number of Observations Read 233 Analysis of Variance Source DF Sum of Mean F Value Pr> F Squares Square Model 3 1038.78 346.26 54.14 |t| Estimate Error Intercept Intercept 1 17.11 0.69 24.72