Consider a hypothetical regression predicting if someone will be married or not by the age of 40, MARRIED? (1 means this person is married by the age of 40 and 0 means this person is not married by the age of 40). The regression is as follows (all variables are statistically significant): MARRIED? = 0.2 + 0.03*EDUCATION - 0.01*BMI Where EDUCATION is the number of years of education someone's had and BMI is their body mass index. Suppose someone had 20 years of education and a BMI of 25.  Complete this sentence: For every additional year of education someone has:... a   ...their chance of getting married by 40 increases by 0.03 percentage points.  b   ...their chance of getting married by 40 increases by 3 percentage points. c   ...their chance of getting married by 40 increases by 0.03. d   ...their chance of getting married by 40 increases by 3%. e   This regression means nothing because the dependent variable is a dummy variable.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
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Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 15PPS
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Consider a hypothetical regression predicting if someone will be married or not by the age of 40, MARRIED? (1 means this person is married by the age of 40 and 0 means this person is not married by the age of 40).

The regression is as follows (all variables are statistically significant):

MARRIED? = 0.2 + 0.03*EDUCATION - 0.01*BMI

Where EDUCATION is the number of years of education someone's had and BMI is their body mass index.

Suppose someone had 20 years of education and a BMI of 25. 

Complete this sentence:

For every additional year of education someone has:...

a  

...their chance of getting married by 40 increases by 0.03 percentage points. 

b  

...their chance of getting married by 40 increases by 3 percentage points.

c  

...their chance of getting married by 40 increases by 0.03.

d  

...their chance of getting married by 40 increases by 3%.

e  

This regression means nothing because the dependent variable is a dummy variable.

 

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