The following table shows a portion of the regression results. MS SS 5,694,717 F Significance F...

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The following table shows a portion of the regression results. MS SS 5,694,717 F Significance F 1,343,176 7,037,893 Regression Residual Total Intercept Bedroom Bath Sq ft df 39 Coefficients Std. Error 300 226 89 0.2 84.0 60.3 55.9 0.09 t-stat (a) (b) (c) (d) p-value (e) (f) (g) (h) Lower 95% 130.03 103.45 -24.24 0.024 Upper 95% 470.79 348.17 202.77 0.39 1. Form the competing hypotheses if we wish to test for whether the number of bedrooms significantly influences rent. 2. Calculate the test statistics for all variables: (a) until (d). 3. Approximate the p-value for all variables: (e) until (h). The following table shows a portion of the regression results. MS SS 5,694,717 F Significance F 1,343,176 7,037,893 Regression Residual Total Intercept Bedroom Bath Sq ft df 39 Coefficients Std. Error 300 226 89 0.2 84.0 60.3 55.9 0.09 t-stat (a) (b) (c) (d) p-value (e) (f) (g) (h) Lower 95% 130.03 103.45 -24.24 0.024 Upper 95% 470.79 348.17 202.77 0.39 1. Form the competing hypotheses if we wish to test for whether the number of bedrooms significantly influences rent. 2. Calculate the test statistics for all variables: (a) until (d). 3. Approximate the p-value for all variables: (e) until (h).

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Form the competing hypotheses if we wish to test for whether the number of bedrooms significantly influences rent Hypothesis test Null hypothesis H0 The number of bedrooms does not significantly influ... View the full answer