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Exercise 30 Calculating Multiple Linear Regression

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Exercise 30 Calculating Multiple Linear Regression

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  • September 10, 2024
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  • 2024/2025
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Exercise 30: Calculating Multiple Linear Regression

1. Write the newly computed regression equation, predicting months to RN to BSN program

completion.

a. Y hat= -4.235x1 + -1.630x2 +17.309

2. Why have the values in the equation changed slightly from the first analysis?

a. Actual values create variance in the equation

3. Using SPSS, create a scatterplot of predicted values and residuals that assists us in identifying

heteroscedasticity. Do the data meet the homoscedasticity assumptions? Provide a rationale

for your answer.

a. Yes, as homoscedasticity reflects equal variance of both variables. For every x value, the

distribution of y values is equally variable.

4. Using the new regression equation, compute the predicated months to RN to BSN program

completion if a student’s number of degrees in 1 and is enrolled in the online program. Show

your calculations.

a. Y hat= -4.235x1 + -1.630x2 +17.309= -4.235(1) + -1.630(1) +17.309= 11.444

5. Using the new regression equation, compute the predicted months to RN to BSN program

completion if a student’s number of degrees is 2 and is enrolled in the in-seat program. Show

your calculations.

a. Y hat= -4.235x1 + -1.630x2 +17.309= -4.235(2) + -1.630(2) +17.309= 29.039

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