a.Y' = 0.476X + 33.272b.Y' = -1.931X + 66.363c.Y' = -0.476X + 33.272d.Y' = -0.432X + 32.856 ___ 10. Refer to Case Study 7-1. If an individual exercises 20 minutes daily, his predicted % body fat woul
5
____ 1. The closer the points on a scatter diagram fall to the regression line, the _________ between the scores.
| a. | higher the correlation |
| b. | lower the correlation |
| c. | correlation doesn't change |
| d. | need more information |
____ 2. The weakest degree of correlation shown below is _________.
| a. | 0.75 |
| b. | -0.33 |
| c. | -0.25 |
| d. | 0.15 |
____ 3. The Spearman Rho correlation is used _________.
| a. | when both variables are dichotomous |
| b. | when both variables are of interval or ratio scaling |
| c. | when one or both variables are only of ordinal scaling |
| d. | when the data is nonlinear |
Case Study 6-1
A traffic safety officer conducted an experiment to determine whether there is a correlation between people's ages and driving speeds. Six individuals were randomly sampled and the following data were collected.
| Age | 20 | 25 | 45 | 46 | 60 | 65 |
| Speed (mph) | 60 | 47 | 55 | 38 | 45 | 35 |
Σ X = 280 Σ Y = 261 Σ XY = 11,573
Σ X2 = 13,528 Σ Y2 = 12,991
NOTE: Feel free to use SPSS to answer these questions
____ 4. Refer to Case Study 6-1. The value of Pearson r equals _________.
| a. | -0.82 |
| b. | -0.70 |
| c. | -0.63 |
| d. | +0.70 |
___ 5. Refer to Case Study 6-1. The proportion of variability of Y accounted for by X is _________.
| a. | 0.49 |
| b. | 0.67 |
| c. | 0.40 |
| d. | -0.49 |
Case Study 6-2
A researcher wanted to know if the order in which runners finish a race is correlated with their weight. She conducts an experiment and the data are given below.
| Finishing order | ||||||
| Weight (lbs) | 110 | 114 | 112 | 108 | 116 | 113 |
____ 6. Refer to Case Study 6-2. What is the appropriate correlation coefficient for this data?
| a. | r |
| b. | rho |
| c. | phi |
| d. | biserial |
____ 7. The regression equation most often used in psychology minimizes _________.
| a. |
|
| b. |
|
| c. |
|
| d. |
|
| e. | none of the above |
(Y - Y')
____ 8. If two variables are ratio scaled and the relationship is linear, what type of correlation coefficient is most appropriate?
| a. | Pearson |
| b. | Spearman |
| c. | eta |
| d. | phi |
Case Study 7-1
A researcher collects data on the relationship between the amount of daily exercise an individual gets and the percent body fat of the individual. The following scores are recorded.
| Individual | |||||
| Exercise (min) x | 10 | 18 | 26 | 33 | 44 |
| % Fat(y) | 30 | 25 | 18 | 17 | 14 |
Put in the missing values below
Σ X = Σ Y = Σ XY =
Σ X2 = Σ Y2 =
NOTE: Feel free to use SPSS to answer these questions
____ 9. Refer to Case Study 7-1. Assuming a linear relationship holds, the least squares regression line for predicting % fat from the amount of exercise an individual gets is _________.
| a. | Y' = 0.476X + 33.272 |
| b. | Y' = -1.931X + 66.363 |
| c. | Y' = -0.476X + 33.272 |
| d. | Y' = -0.432X + 32.856 |
___ 10. Refer to Case Study 7-1. If an individual exercises 20 minutes daily, his predicted % body fat would be _________.
| a. | 21.63 |
| b. | 27.74 |
| c. | 27.88 |
| d. | 23.75 |
____ 11. Refer to Case Study 7-1. The value for the standard error of estimate in predicting % fat from daily exercise is _________.
| a. | 3.35 |
| b. | 4.32 |
| c. | 2.14 |
| d. | 1.66 |
| e. | none of above |
____ 12. The assumption of homoscedasticity is that _________.
| a. | the range of the Y scores is the same as the X scores |
| b. | the X and Y distributions have the same mean values |
| c. | the variability of Y doesn't change over the X scores |
| d. | the variability of the X and Y distributions is the same |
____ 13. The higher the standard error of estimate is,
| a. | the more accurate the prediction is likely to be |
| b. | the less accurate is the prediction is likely to be |
| c. | the less confidence we have in the accuracy of the prediction |
| d. | the more confidence we have in the accuracy of the prediction |
| e. | b and c |
14. (7 Points) A statistics professor conducts a study to investigate the relationship between the performance of students on his exams and their anxiety. Ten students from his class are selected for the experiment. Just prior to taking the final exam, the 10 students are given an anxiety questionnaire. Here are final exam and anxiety scores for the students.
Anxiety Final Exam
28 82
41 58
35 63
39 89
31 92
42 64
50 55
46 70
45 51
37 72
Put in the missing values below
Σ X = Σ Y = Σ XY =
Σ X2 = Σ Y2 =
Pearson r for these two variables is
Write the least squares regression equation using anxiety predicting the final exam.
If anxiety level was 49, what is the predicted final exam score.
d) What percent of the variance in the final exam is accounted for by anxiety?
NOTE: Feel free to use SPSS to answer these questions
