Simple linear regression equation


1. Consider the following data measured in a sample of n=25 undergraduates in an on-campus survey of health behaviors. Enter the data into an Excel worksheet for analysis.

ID Age Female Sex Year in School GPA Current Smoker # YYY Exercise per Week # YYY Number of Drinks per Week # YYY Coffee per Week

1 18 1 Fr 3.85 1 7 3 3

2 21 0 Jr 3.27 1 3 2 4

3 19 1 So 2.90 0 0 4 7

4 22 0 Sr 3.65 1 0 2 4

5 21 1 Sr 3.41 1 0 1 3

6 20 0 Jr 3.20 0 2 5 8

7 19 1 Jr 2.89 1 1 4 10

8 17 0 Fr 3.75 0 6 0 0

9 18 0 So 4.00 0 6 2 6

10 17 1 So 3.18 0 3 5 7

11 21 0 Jr 2.58 1 3 12 12

12 22 1 Sr 2.98 0 2 3 4

13 19 0 Fr 3.16 1 2 0 6

14 21 1 Jr 3.36 1 3 1 2

15 22 1 So 3.72 0 6 3 0

16 19 0 So 3.30 1 4 0 6

17 16 0 Fr 3.28 0 4 0 5

18 22 0 Sr 2.98 0 0 8 5

19 17 1 Fr 3.90 0 7 0 2

20 20 1 Sr 3.78 1 4 6 2

21 21 1 So 3.26 1 2 3 4

22 23 0 Jr 3.01 0 1 9 7

23 23 0 Sr 3.83 1 5 4 4

24 17 1 Fr 3.76 0 5 2 1

25 22 1 Sr 3.05 0 1 5 5

2. Estimate the simple linear regression equation relating number of cups of coffee per week to GPA (Consider GPA the dependent or outcome variable).

3. Estimate the simple linear regression equation relating female sex to GPA (Consider GPA the dependent or outcome variable).

4. Estimate the multiple linear regression equation relating number of cups of coffee per week, female sex and number of hours of exercise per week to GPA (Consider GPA the dependent or outcome variable).

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Mathematics: Simple linear regression equation
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