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For a sample of 20 New England cities, a sociologist studies the crime rate in each...

For a sample of 20 New England cities, a sociologist studies the crime rate in each city (crimes per 100,000 residents) as a function of its poverty rate (in %) and its median income (in $1,000s). A portion of the regression results is shown in the accompanying table. Use Table 2 and Table 4. ANOVA df SS MS F Significance F Regression 2 294.3 147.2 9.73E-01 Residual 17 91,413.94 5,377.29 Total 19 91,708.30 Coefficients Standard Error t Stat p-value Lower 95% Upper 95% Intercept 760.09 93.0941 8.1648 0.0000 563.68 956.50 Poverty −0.0245 5.8042 −0.0042 0.9967 −12.27 12.22 Income 3.2598 14.1819 0.2299 0.8209 −26.66 33.18 a. Specify the sample regression equation. (Negative values should be indicated by a minus sign. Report your answers to 4 decimal places.) Crimeˆ Crime ^ = + Poverty + Income b-1. Choose the appropriate hypotheses to test whether the poverty rate and the crime rate are linearly related. H0: β1 ≥ 0; HA: β1 < 0 H0: β1 ≤ 0; HA: β1 > 0 H0: β1 = 0; HA: β1 ≠ 0 b-2. At the 5% significance level, what is the conclusion to the hypothesis test? Do not reject H0Picture we cannot conclude the poverty rate and the crime rate are linearly related. Reject H0Picture the poverty rate and the crime rate are linearly related. Do not reject H0Picture we can conclude the poverty rate and the crime rate are linearly related. Reject H0Picture the poverty rate and the crime rate are not linearly related. c-1. Construct a 95% confidence interval for the slope coefficient of income. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Confidence interval to

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