A researcher used stepwise regression to create regression models to predict CarTheft (thefts per 1,000) using four predictors: Income (per capita income), Unem (unemployment percent), Pupil/Tea (pupil-to-teacher ratio), and Divorce (divorces per 1,000 population) for the 50 U.S. states. Interpret these results.

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Regression Analysis-Stepwise Selection (best model of each size) 50 observations CarTheft is the dependent variable p-values for the coefficients Nvar Income Unem PupiVTea Divrce Std. Err Adj R2 R 0013 O15 0000 0007 0323 0003 167.482 218 234 152.362 353 379 144.451 143.362 7474 0018 015 418 454 4 1987