Exercise 29: Calculating Simple Linear Regression
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.
The frequency distribution did not show a statistically significant based on the p value
of 0.357.
2. State the null hypothesis where age at enrollment is used to predict the time for completion of
an RN to BSN program.
Null Hypothesis = Student’s age at enrollment does not predict the # of months until
completion of an RN to BSN program.
3. What is b as computed by hand (or using SPSS)?
A (constant) = 11.763
B (student age) = .047
4. What is a as computed by hand (or using SPSS)?
A (constant) = 11.763
B (student age) = .047
5. Write the new regression equation.
Y = 0.47(age) + 11.763
6. How would you characterize the magnitude of the obtained R2 value? Provide a rationale for
your answer.
The characterization of the magnitude of the obtained R2 value is small when observed
according to the description offered in the lesson.
7. How much variance in months to RN to BSN program completion is explained by knowing
the student’s enrollment age?
Knowing the student’s enrollment age explains the variance in months of RN to BSN
program completion, which is 1.2%.
8. What was the correlation between the actual y values and the predicted y values using the
new regression equation in the example?
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.
The frequency distribution did not show a statistically significant based on the p value
of 0.357.
2. State the null hypothesis where age at enrollment is used to predict the time for completion of
an RN to BSN program.
Null Hypothesis = Student’s age at enrollment does not predict the # of months until
completion of an RN to BSN program.
3. What is b as computed by hand (or using SPSS)?
A (constant) = 11.763
B (student age) = .047
4. What is a as computed by hand (or using SPSS)?
A (constant) = 11.763
B (student age) = .047
5. Write the new regression equation.
Y = 0.47(age) + 11.763
6. How would you characterize the magnitude of the obtained R2 value? Provide a rationale for
your answer.
The characterization of the magnitude of the obtained R2 value is small when observed
according to the description offered in the lesson.
7. How much variance in months to RN to BSN program completion is explained by knowing
the student’s enrollment age?
Knowing the student’s enrollment age explains the variance in months of RN to BSN
program completion, which is 1.2%.
8. What was the correlation between the actual y values and the predicted y values using the
new regression equation in the example?
