Chapter 3

Multiple Regression Assignment

For a sample of over 160 college students, the following variables were measured:

Y = height

X₁ = mother's height

X₂ = father's height

X₃ = 1 if male, 0 if female

The goal is to predict student's height using the mother's and father's heights, and sex, where sex is categorized using the variable "male" = 1 if male, 0 if female.

Question 1

The regression model is __________________________________________

First look at some plots of the original data to see if there are outliers. The plots are:

Separate histograms of male and female students' heights.

Histogram of mothers' heights.

Histogram of fathers' heights.

Question 2

Are there outliners? ________________________

If so, provide the following information.

Specify the outlier________________________________________

Why do you consider this an outlier?_____________________________________________________

Repeat the above questions for each outlier you find.

Regress command results (remember that we now have n = 165 cases; we removed one outlier): Source | SS df MS Number of obs = 165 WWWWwww F( 3, 161) 104.38 Model 1679. 17741 3 559. 725803 Prob > F = 0. 0000 Residual 863 . 31653 161 5. 36221447 R-squared = 0 . 6604 Adj R-squared = 0 . 6541 Total | 2542 . 49394 164 15 .5030118 Root MSE = 2 . 3156 height I Coef. Std. Err. [95% Conf. Interval] momheight - . 2996154 . 0687614 4.36 0. 000 . 1638247 . 435406 dadheight - wWwwwwwww . 412135 . 0510733 8.07 0. 000 . 311275 . 512995 male 5 . 298218 . 3637717 14.56 0. 000 4.579839 6.016597 constant 16.96746 4. 658309 3. 64 0.000 7. 768196 26.16673