Reference no: EM131130117

1. From Table 3, how much variability in Phyfu does BMI account for?
a) -38%
b) 14%
c) 62%
d) 38%

2. From the Results section, the range for age was:
a) 36 years
b) 40 years
c) 63 years
d) 76 years

3. From Table 4, what was the unstandardized slope for BMI when predicting PCS in Model 3?
a) -0.67
b) 2.16
c) -1.59
d) 0.09

4. From the Results section, the 7.6 year SD for age means:
a) Body weight is 7.6% variable.
b) The middle 68% of the scores fall between 55.6 years and 70.8 years.
c) The middle 95% of the scores fall between 48.0 years and 78.4 years.
d) Both b and c

5. From Table 3, the r for BMI and WI was -0.090 and was not statistically significant. What does this mean?
a) Those with a high BMI tended to have a high WI score.
b) Those with a high BMI tended to have a low WI score.
c) BMI and WI were not related.

6. From the Results section, third paragraph, for whom was age more scattered (or more variable)?
a) Those participants with a BMI of 25-30
b) Those participants with a BMI of > 35
c) The variability of their distributions was the same.

7. From Table 3, which variable (BMI, PA, WI, or DD) is the most highly related to Phyfu? [See the Table footnote for the definition of abbreviations.]
a) BMI
b) PA
c) WI
d) DD

8. From Table 4, how much variability does BMI account for in PCS above what age and sex account for?
a) 1%
b) 15%
c) 16%
d) 17%
9.

9. From Table 4, which of the following is a y variable?
a) Vitality
b) Age
c) Sex
d) BMI

10. Based on Table 4, which variable accounted for the most variability in PCS?
a) Age and sex
b) BMI
c) PA
d) None were related

11. From Table 4, were age and sex significant predictors of PCS?
a) Yes
b) No

12. From Table 4, age and sex (together) explain the least amount of variability for what variable?
a) PCS
b) Physical function
c) MCS
d) Vitality
e) Psychological well-being

13. From Table 3, the r for PA and age was -0.252 and was statistically significant. What does this mean?
a) Older people tended to be more active.
b) Older people tended to be less active.
c) Age and physical activity were not related.

14. If given that the median for age was 50 years with a mean of 63.2 years, what would this distribution look like?
a) A platykurtic curve
b) A normally distributed curve
c) A leptokurtic curve
d) A positively skewed curve

15. From Table 3, which variable (BMI, PA, WI, or DD) is the strongest positive relationship with Phyfu? [See the Table footnote for the definition of abbreviations.]
a) BMI
b) PA
c) WI
d) DD

16. Based on the data in the Results section, how likely is it that a person would have been a diabetic for 45 years?
a) Very likely since this number is well within plus or minus 1 SD of the mean
b) Unlikely since this number is well within plus or minus 1 SD of the mean
c) Very likely since this number is well outside of plus or minus 3 SD of the mean
d) Unlikely since this number is well outside plus or minus 3 SD of the mean

17. The results of this study can be generalized to whom?
a) All men and women with type II diabetes
b) Men and women over 20 years
c) All people with type II diabetes
d) Men and women between 36 and 76 years with type II diabetes

18. In this study, 370 people had quality of life and physical activity levels measured. These 370 people were what?
a) A sample
b) A randomly selected and representative sample
c) A population
d) A random population

19. From Table 4, age, sex, and BMI accounted for the largest amount of variability for which variable?
a) PCS
b) Physical function
c) MCS
d) Vitality
e) Psychological well-being

20. Based on Table 4, age, sex, and BMI all together account for 8% of the variability in Vitality. If the R squared is 8%, what would the correlation coefficient (r) be for this analysis?
a) 0.08
b) 0.0064
c) 0.64
d) 0.28

Attachment:- Eckert.pdf