1. *********Use 2 decimal places for all questions.*********
The following applies to Questions 1 to 3: An investigator sets out to test the hypothesis that the time it takes to perform a complex motor task decreases linearly as a function of length of time in training. To evaluate this hypothesis, a total of 40 participants are assigned randomly to 4 conditions (10 in each) representing 2, 4, 6, and 8 hours of training. Suppose the investigator reports that the fitted regression line shows that the time to complete the task drops from 20 minutes after 2 hours to 10 minutes after 6 hours. HINT: Drawing a graph may help.
1. What is the estimate of the α parameter of this regression model?
1. 2. What is the estimate of the β parameter of this regression model?
1. 3. What is the predicted time to complete the task after 7 hours of training?
1. The following applies for Questions 4 to 7. An investigator administers tests of spatial and numerical ability to a sample of 150 children. The standard deviations were 9.4 for the spatial ability test and 5.3 for the numerical ability test. The sum products was 3736.0.
4. What is the value of the covariance between the two measures?
1. 5. What is the value of the effect size between the two measures?
1. 6. What is the regression coefficient for predicting spatial ability from numerical ability?
1. 7. What is the regression coefficient for predicting numerical ability from spatial ability?
1. The following applies to Questions 8 to 10: A psychologist wishes to predict children's academic performance from their language abilities. In order to formulate a prediction rule, 200 children's grades are obtained, as well as their scores on an assessment of their language abilities. For language abilities, the mean was 2.60 and the standard deviation was 0.68. For grades, the mean was 2.20 and the standard deviation was 0.76.The product-moment correlation for this sample was found to be r = 0.63.
8. What is the slope of the regression line for predicting grades from language abilities?
1. 9. What is the intercept of the regression line for predicting grades from language abilities?
1. 10. A child obtained a language score of 3.2. What is her predicted grade?
1. The following applies to Question 11 to 16: An investigator administers a test of reasoning ability to a sample of 120 children ranging in age from 7 to 12 years. A regression analysis, predicting test scores from age, gives a value of 41.3 for SSregression and a value of 205.0 for SSe.
11. What is the value of R2 for these data?
1. 12. What is the standard error of the estimate?
1. 13. Find the F-ratio to evaluate the significance of the linear relation between age and reasoning ability.
1. 14. Find the relevant critical tabled value for α = .05.
1. 15. Can test scores be predicted from age?
1. 16. What is the variance of the test scores?
1. The following applies to Question 17 to 21: Suppose there were 170 students in Psyo2000, and that their final grades had a variance of 38.00. Now suppose that grades in Psyo2501 correlated at r = 0.78 with those of Psyo2000.
17. What is the value of R2 for these data?
1. 18. What is the standard error of the estimate?
1. 19. Find the F-ratio used to predict Psyo2000 marks from Psyo2501 marks.
1. 20. Find the relevant critical tabled value for α = .05.
1. 21. Can one predict Psyo2000 grades from Psyo2501 grades?
|Due By (Pacific Time)
||12/02/2013 12:00 am