A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used...
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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 α = 0.01 with 31 d.f. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p-values to 4 decimal places.) |
| Predictor | Coefficient | SE | tcalc | p-value | |
| Intercept | 4,414.1682 | 797.4268 | |||
| AgeMed | -25.674 | 12.4815 | |||
| Bankrupt | 17.8059 | 12.3818 | |||
| FedSpend | -0.0170 | 0.0193 | |||
| HSGrad% | -30.1905 | 7.1988 | |||
| (b-1) |
What is the critical value of Student's t in Appendix D for a two-tailed test at α = 0.01 with 31 d.f? (Round your answer to 3 decimal places.) |
| t-value = |
| (b-2) | Choose the correct option. | ||||||
|
Homework Answers
a)
| Predictor | Coefficient | SE | tcalc | p-value |
| Intercept | 4,414.17 | 797.4268 | 5.5355 | 0 |
| AgeMed | -25.674 | 12.4815 | -2.057 | 0 .048 |
| Bankrupt | 17.8059 | 12.3818 | 1.4381 | 0.16 |
| FedSpend | -0.017 | 0.0193 | -0.881 | 0.386 |
| HSGrad% | -30.1905 | 7.1988 | -4.194 | 0 |
b)
t-critical = 3.022
Only HSGrad% differs significantly from zero
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A regression model to predict Y, the state burglary
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A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used...
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