A regression model to predict Y, the state burglary rate per 100,000 people for

Question

A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used the following four state predictors: X1 median age in 2005, X2 number of 2005 bankruptcies, X3 2004 federal expenditures per capita (a leading predictor), and X4 2005 high school graduation percentage (a) Fill in the values in the table given here for a two-tailed test at = 0.01 with 40 df. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "O" wherever required. Round your t-values to 3 decimal places and p-values to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad96 Coefficient SE value 4,459.7813 797.7352 26.190 12.3168 16.9037 2.6186 0.0133 7.1255 0.0155 30.9882 (b-1) What is the critical value of Student's t in Appendix D for a two-tailed test at = 0.01 with 40 df? (Round your answer to 3 decimal places.) t-value (b-2) Choose the correct option. Only Bankrupt differs significantly from zero. Only FedSpend differs significantly from zero Only HSGra0% differs significantly from zero.

Explanation / Answer

as test statistic t =coeff/SE

hence :

b--1) t value =2.704

b-2)

only HS grad differs significantly from 0/

predictor coefficent SE tcalc p-value intercept 4459.7813 797.7352 5.591 0.0000 agemed -26.19 12.3168 -2.126 0.0397 bankrupt 16.9037 12.6186 1.340 0.1879 fedspent -0.0155 0.0133 -1.165 0.2508 HS grad -30.9882 7.1255 -4.349 0.0001

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