### Linear Statistical Models: Regression

### Prediction Practice: Part 2

###
Predicting Standardized Writing Test Score

write, read and math are standardized tests, normed with mean = 50 and sd = 10.

gender is coded 1=male 2=female

Regression equation: write' = 6.45 + 5.4gender + .3read + .4math

1) What is the predicted write score for females with read=60 and math=55

write' = 6.45 + 5.4*2 + .3*60 + .4*55

write' = 6.45 + 10.8 + 18 + 22

write' = 57.25

2) What is the predicted write score for males with read=45 and math=50
3) What is the predicted write score for females with read=50 and math=50

4) What is the predicted write score for males with read=70 and math=80

5) What is the predicted write score for gender=2, read=70 and math=80

6) Write the regression prediction equation for predicting crime from
the following regression results:

Source | SS df MS Number of obs = 51
---------+------------------------------ F( 3, 47) = 38.19
Model | 6898744.52 3 2299581.51 Prob > F = 0.0000
Residual | 2829730.23 47 60207.0261 R-squared = 0.7091
---------+------------------------------ Adj R-squared = 0.6906
Total | 9728474.75 50 194569.495 Root MSE = 245.37
------------------------------------------------------------------------------
crime | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
hsgrad | -5.522098 9.8632 -0.560 0.578 -25.3643 14.3201
poverty | .7805124 14.03845 0.056 0.956 -27.4612 29.02223
single | 170.2942 20.77943 8.195 0.000 128.4914 212.097
_cons | -906.0376 846.7254 -1.070 0.290 -2609.429 797.3542
------------------------------------------------------------------------------

Linear Statistical Models Course

Phil Ender, 18dec99