Question

I would really appreciate if you do it in SPSS, otherwise do it in Excel. Thanks!...

I would really appreciate if you do it in SPSS, otherwise do it in Excel. Thanks!

Run the regression again without the potential confounding variable and discuss the impact on the coefficient of the primary independent variable. Did it change? If so, to what extent did it change? Based on this, do you think the added variable confounds the association between the independent and dependent variables? Interpret the results.

Independent variable: Minutes exercise

Dependent variable: Annual income

Counfonding variable: Education Level

Minutes_Exercise Annual_Income* Education_Level***
90 51000 2
50 23000 2
65 35000 3
20 10000 1
50 28000 1
25 5000 2
110 46000 3
50 36000 1
40 51000 2
80 12000 2
120 78000 3
80 34000 1
60 15000 1
150 28000 3
75 28000 2
80 24000 1
110 55000 2
80 62000 3
100 32000 2
0 7000 1
50 17000 2
200 64000 3
60 5000 2
65 14000 1
40 20000 1
65 72000 3
70 85000 3
45 15000 1
75 64000 3
50 27000 3

Homework Answers

Answer #1

Independent variable: Minutes exercise

Dependent variable: Annual income

Counfonding variable: Education Level

Regression output without Counfonding variable:

Regression Statistics
Multiple R 0.50650506
R Square 0.256547376
Adjusted R Square 0.229995497
Standard Error 20073.22859
Observations 30
ANOVA
df SS MS F Significance F
Regression 1 3893200499 3893200499 9.662117396 0.004288622
Residual 28 11282166167 402934506
Total 29 15175366667
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 13584.73078 7737.415446 1.755719448 0.09007202 -2264.64628 29434.10784
Minutes_Exercise 294.8761377 94.86444593 3.108394665 0.004288622 100.5551291 489.1971462

Annual income = 13584+294.87*Minutes exercise.

R square value is only 0.25. Hence this is not a effective equation

Regression output with Counfonding variable:

Regression Statistics
Multiple R 0.678587671
R Square 0.460481227
Adjusted R Square 0.420516873
Standard Error 17413.69747
Observations 30
ANOVA
df SS MS F Significance F
Regression 2 6987971457 3493985728 11.52229888 0.00024104
Residual 27 8187395210 303236859.6
Total 29 15175366667
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -4015.193133 8683.64939 -0.46238545 0.647509608 -21832.56995 13802.18368
Education_Level*** 14595.47627 4568.724917 3.194649827 0.003546758 5221.227061 23969.72547
Minutes_Exercise 133.5161104 96.55977653 1.38273011 0.178078032 -64.60818572 331.6404066

Annual income = -4015.19+133.51*Minutes exercise + 14595.47*Education_Level

So coefficient of primary Independent variable changed from 133.51 to 294.87

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