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, X27 number of 2005 bankruptoes, 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 -001 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.) p-value Intercept AgeMed Bankrupt FedSpend HSGra0% 4,459 7813 797.7352 26 190 12.3168 69037126186 0.015500133 71255 -309882 ! (b-1) What is the critical value of Student's t in AppendMD for a two-tailed test at 0 01 with 40 d t? (Round your answer to 3 decimal places.) t-value (b-2) Choose the correct option. OOnly Bankrupt differs significantly from zero Only FedSpend differs significantly from zero Only HSGra0% difers significantly from zero. Type here to search

Explanation / Answer

(a) t cal= coefficient / corresponding SE

b-2: Only HAGrad% differs significantly from zero. Because, It has p value less than alpha.

alpha = 0.01

Predictor Coefficient SE tcalc p- value intercept 4459.7813 797.7352 5.590553482 <0.0001 AgeMed -26.19 12.3168 -2.126363991 0.0397 Bankrupt 16.9037 12.6186 1.339586008 0.1879 FedSpend -0.0155 0.0133 -1.165413534 0.2508 HSGrad% -30.9882 7.1255 -4.348915866 < 0.0001

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