Are New Jersey bank executives averse to minorities? If they are, then at least

Question

Are New Jersey bank executives averse to minorities? If they are, then at least one way this bias might be observed is in where bank executives choose to set up branches: Banks would be more scarce in populations with higher percentages of minorities. Let's suppose we are interested in starting a new bank that focuses on lending to minorities is this an lending to and banking with minority populations? Below is the dataset from the Excel file "NJBank" in the "Excel Files" section of BlackBoard market in New Jersey, or are banks there already focused on Number of 6 of Minority Population, x County Residents per Bank Branch, y 23.3 13.0 17.8 23.4 3073 2095 2905 3330 1321 2557 3474 3068 3683 1998 2607 3154 2609 2253 2317 3307 2511 2333 2568 3048 2349 Atantic Bergen Bulington Camden Cape May Cumberland Essex 28.5 48.8 10.7 33.2 Hudso Mercer Middlesex Monmouth Morris Ocean paasic Salem Somerset Sussex Union Warren 24.9 12.6 8.2 4.7 16.7 12.0 25.6 2.8 We are interested in using the "% of Minority Population" variable to predict bank scarcity ( Number of Residents per Bank Branch"). Conduct a regression analysis using MS Excel, with "X" (independent) and "Y" (dependent) variables as indicated in the labels for each variable Based on the MS Excel regression output that you generated, the regression model is significant because: The p-value for the F-test on the significance of the model is

Explanation / Answer

We have fitted a regression model of Y on X using excel. Below is the regression output generated in MS excel.

Observe that the p-value in ANOVA table is 0.000197 < 0.05, hence we can conclude that:

The model is significant because

The p-value for F-test on the significance of the model is << 0.05

The first option is correct.

SUMMARY OUTPUT Regression Statistics Multiple R 0.725629 R Square 0.526538 Adjusted R Square 0.501619 Standard Error 400.2546 Observations 21 ANOVA df SS MS F Significance F Regression 1 3385090 3385090 21.12991 0.000197 Residual 19 3043870 160203.7 Total 20 6428961 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 2082.015 159.107 13.08563 5.92E-11 1749.001 2415.03 X 35.28774 7.676707 4.596728 0.000197 19.2202 51.35527

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