document.write( "Question 178531This question is from textbook
\n" ); document.write( ": 12.50 In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks. (a) Write the fittedregression equation. (b) State the degrees of freedom for a two- tailed test for zero slope, and use Appendix D to find the critical value at α= .05. (c) What is your conclusion about the slope? (d) Interpret the 95 percent confidence limits for the slope. (e) Verify that F = t2 for theslope. (f) In your own words, describe the fit of this regression.
\n" ); document.write( "R2 0.519
\n" ); document.write( "Std. Error 6.977
\n" ); document.write( "n 64
\n" ); document.write( "ANOVA table
\n" ); document.write( "Source SS df MS F p-value
\n" ); document.write( "Regression 3,260.0981 1 3,260.0981 66.97 1.90E-
\n" ); document.write( "Residual 3,018.3339 62 48.6828
\n" ); document.write( "Total 6,278.4320 63
\n" ); document.write( "Regression output confidence interval
\n" ); document.write( "variables coefficients std. error t (df =62) p-value 95% lower 95% upper
\n" ); document.write( "Intercept 6.5763 1.9254 3.416 .0011 2.7275 10.4252
\n" ); document.write( "X1 0.0452 0.0055 8.183 1.90E-11 0.0342 0.0563
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Algebra.Com's Answer #134100 by stanbon(75887)\"\" \"About 
You can put this solution on YOUR website!
In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks.
\n" ); document.write( "(a) Write the fitted regression equation.
\n" ); document.write( "Y = 6.5763 + 0.0452X
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\n" ); document.write( "(b) State the degrees of freedom for a two- tailed test for zero slope, and use Appendix D to find the critical value at α= .05.
\n" ); document.write( "df = 62 ; crit. value = 1.96 (I do not have the same D-chart you may have)
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\n" ); document.write( "(c) What is your conclusion about the slope?
\n" ); document.write( "Since p-value = 1.9E-11, reject hypothesis that the slope is zero
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\n" ); document.write( "(d) Interpret the 95 percent confidence limits for the slope.
\n" ); document.write( "With 95% confidence we can say the slope is between 0.0342 and 0.0563
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\n" ); document.write( "(e) Verify that F = t2 for the slope.
\n" ); document.write( "66.97 = 8.8183^2
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\n" ); document.write( "(f) In your own words, describe the fit of this regression.
\n" ); document.write( "Since R^2 is 51.9% the fit is good.\r
\n" ); document.write( "\n" ); document.write( "---------------
\n" ); document.write( "R2 0.519
\n" ); document.write( "Std. Error 6.977
\n" ); document.write( "n 64
\n" ); document.write( "-------------------------
\n" ); document.write( "ANOVA table
\n" ); document.write( "Source........ SS.... df MS......... F.. p-value
\n" ); document.write( "Regression 3,260.0981 1 3,260.0981 66.97 1.90E-
\n" ); document.write( "Residual.. 3,018.3339 62 48.6828
\n" ); document.write( "Total..... 6,278.4320 63
\n" ); document.write( "-----------------------------------
\n" ); document.write( "Regression output confidence interval
\n" ); document.write( "variables coefficients std. error t (df =62) p-value 95% lower 95% upper
\n" ); document.write( "Intercept 6.5763 1.9254 3.416................0.0011.. 2.7275... 10.4252
\n" ); document.write( "X1....... 0.0452 0.0055........... 8.183.....1.90E-11.. 0.0342.... 0.0563\r
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\n" ); document.write( "Cheers,
\n" ); document.write( "Stan H.
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