# statistics

Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition

Exercise 29: Calculating Simple Linear Regression

The following questions refer to the section called “Data for Additional Computational Practice” in Exercise 29 of Grove & Cipher, 2017.

1.     If you have access to SPSS, compute the Shapiro-Wilk test of normality for the variable age (as demonstrated in Exercise 26). If you do not have access to SPSS, plot the frequency distributions by hand. What do the results indicate?

A.   The distribution significantly deviated from normality.

B.    The distribution did not significant from normality.

2.     State the null hypothesis where age at enrollment is used to predict the time for completion of an RN to BSN program.

A.   Age at enrollment predicts the number of months until completion of an RN to BSN program.

B.    Age at enrollment does not predict the number of months until completion of an RN to BSN program.

3.     What is b as computed by hand (or using SPSS)?

A.   0.027

B.    0.037

C.    0.047

D.   0.057

4.     What is a as computed by hand (or using SPSS)?

A.   10.76

B.    11.76

C.    12.76

D.   13.76

5.     Write the new regression equation.

A.     ŷ = 0.027x + 10.76

B.    ŷ = 0.037x + 10.76

C.    ŷ = 0.047x + 11.76

D.   ŷ = 0.057x + 11.76

6.     How would you characterize the magnitude of the obtained R2 value? Provide a rationale for your answer.

A.   R2 value is very low.

B.    R2 value is very high.

7.     How much variance in months to RN to BSN program completion is explained by knowing the student’s enrollment age?

A.   1.2%

B.    2.4%

C.    12%

D.   24%

8.     What was the correlation between the actual y values and the predicted y values using the new regression equation in the example?

A.   0.11

B.    0.155

C.    0.346

D.   0.49

9.     Write your interpretation of the results as you would in an APA-formatted journal.