The following regression looks at the murder rate in different states, and relat

Question

The following regression looks at the murder rate in different states, and relates it to the High School graduation rate:

A. Interpret the regression coefficient.

B. How much of the variation is explained by this one variable?

Now look at this model:

We now add Illiteracy rate:

D. What has happened in the model?

E. What should we do?

Model 1 OLS, using observations 1-50 Dependent variable Murder coefficient std. error t-ratio p-value 19.2224 3.09249 6.216 1.17 Const. 0.0003 -3.873 HSGrad 0.223024 0.0575813 Mean dependent var 7.378000 S. D. dependent var 3.691540 Sum squared resid 508.7450 S.E of regression. 3.2555 88 R-squared 0.238116 Adjusted R-squared 0.2222 43 F (1 48) 15 P-value (F) 0.000325 261.8901 Log-likelihood 128.9450 Akaike criterion 263.3463 Schwarz criterion 265.7141 Hannan-Quinn

Explanation / Answer

a) For unit increase in the value pf High School Graduation rate, the murder rate in different states will decrease 0.223024 unit.

b) 23.81% of variation of the murder rate in different states can be explained by the regression equation with one predictor HSGrad.

c) After adding income as another predictor, we get R2=24.66%, which does not significantly increase, so we can say income has no significant effect to predict the murder rate in different states

d) Adding other predictor Illitercay in the regression equation R2 increases significantly, so Illitercay can be considered as an important predictor to predict the murder rate in different states.

e) so we should use HSGrad and Illitercay as predictors in the regression equation.

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