1. Which variables were significant in your model? (Use an alpha of 1% to draw your conclusions.) 2. In the regression model you ran, the binary variables were defined as Female = 0, Male = 1. Using ONLY the information from your regression output, write the regression equation for a model with the OPPOSITE definition of the binary variables (Male = 0, Female = 1).

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter4: Polynomial And Rational Functions
Section4.6: Variation
Problem 37E
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1. Which variables were significant in your model? (Use an alpha of 1% to draw your conclusions.)

2. In the regression model you ran, the binary variables were defined as Female = 0, Male = 1. Using ONLY the information from your regression output, write the regression equation for a model with the OPPOSITE definition of the binary variables (Male = 0, Female = 1). 

SUMMARY OUTPUT
Regression Statistics
Multiple R
0.357056623
R Square
0.127489432
Adjusted R Square
0.122063371
Standard Error
5.662140623
Observations
810
ANOVA
df
SS
MS
F
Significance F
Regression
5 3766.35143
753.2702857
23.495762
4.4032E-22
Residual
804 25776.1085
32.05983643
Total
809 29542.4599
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95% Lower 95.0% Upper 95.0%
Intercept
-0.015534766 0.42318834
-0.036708871 0.97072625
-0.8462192 0.81514964
-0.8462192 0.81514964
Gender (Male = 1)
0.985870743
0.4014699
2.455652934 0.01427351 0.19781787 1.77392362 0.19781787 1.77392362
Exercise
-0.00742009 0.00118168
-6.279247486 5.5636E-10
-0.0097396
-0.0051005
-0.0097396
-0.0051005
Fast food
0.353544316 0.07335589
4.819576149
1.72E-06 0.20955264 0.49753599 0.20955264 0.49753599
Alcohol
0.194136078 0.08498657
2.284314702 0.02261287 0.02731432 0.36095783 0.02731432 0.36095783
Junk Food
0.330639265 0.08398493
3.936888006
8.9697E-05 0.16578365 0.49549488 0.16578365 0.49549488
Transcribed Image Text:SUMMARY OUTPUT Regression Statistics Multiple R 0.357056623 R Square 0.127489432 Adjusted R Square 0.122063371 Standard Error 5.662140623 Observations 810 ANOVA df SS MS F Significance F Regression 5 3766.35143 753.2702857 23.495762 4.4032E-22 Residual 804 25776.1085 32.05983643 Total 809 29542.4599 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.015534766 0.42318834 -0.036708871 0.97072625 -0.8462192 0.81514964 -0.8462192 0.81514964 Gender (Male = 1) 0.985870743 0.4014699 2.455652934 0.01427351 0.19781787 1.77392362 0.19781787 1.77392362 Exercise -0.00742009 0.00118168 -6.279247486 5.5636E-10 -0.0097396 -0.0051005 -0.0097396 -0.0051005 Fast food 0.353544316 0.07335589 4.819576149 1.72E-06 0.20955264 0.49753599 0.20955264 0.49753599 Alcohol 0.194136078 0.08498657 2.284314702 0.02261287 0.02731432 0.36095783 0.02731432 0.36095783 Junk Food 0.330639265 0.08398493 3.936888006 8.9697E-05 0.16578365 0.49549488 0.16578365 0.49549488
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