A model was developed to predict the length of a sentence (the response variable) for a male convicted of assault using the following predictor variables: age (in years), number of prior felony convictions, whether the criminal was married or not (1 = married), and whether the Criminal was employed or not (1 = employed).The table below shows the regression output. (a) Write the regression model.
(b) Using45degreesof freedom, find the p-value for each coefficient. Using an α = .01, which predictor variable(s) are notsignificant predictors of length of sentence?
(c) Interpret the coefficient of Married.
(d) How much shorter is the sentence if The criminal is employed?
(e) Predict the length of sentence for an unmarried, unemployed, 25-year old male with one prior conviction. Show your calculations. Sentencing
Variable Coefficient Standard Error tStatistic
Intercept 3.2563 4.3376 0.751
Age 0.5219 0.1 046 4.989
Convictions 7.7412 1.0358 7.474
Married? –6.0852 2.5809 –2.358
Employed? –14.3402 2.5356 –5.656