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An analyst for a shopping district would like to determine the rent that should be charged for retail spaces depending on how close they are to parking. The analyst takes a random sample of retail spaces in similar shopping districts and measures the monthly rent (S) and distance from parking (in yards) for each retail space. This is the same regression you worked with in Worksheet #9. Here is the complete Excel output for this regression: SUMMARY OUTPUT Regression Stotistics Multiple R RSquare 0.7076 0.5007 Adjusted R Square 0.4918 Standard Error 978.8761 Observations 58 ANOVA Significance SS 53809748.97 53809748.97 df MS Regression 56.1572 5.28E-10 Residual 56 53659115.74 958198.4954 Total 57 107468864.7 Coefficients Standard Error t Stat P value Lower 95% Upper 95% 15502.6 8.37 Intercept 15003.10 249.3464 60.17 14E-52 14503.59 Distance -11.42 1.5239 7.49 5.28E-10 -14.47 NOTE: Excel uses scientific notation for very small numbers. So the p-value = 5.28E-10 = 5.28 x 10 10 - 0.000000000528. In the hypothesis test, you may truncate that to 0.000. Very tiny p-values with more than four zeroes after the decimal are often expressed as 0.000 or .000 when they are reported and interpreted.

An analyst for a shopping district would like to determine the rent that should be charged for retail spaces depending on how close they are to parking. The analyst takes a random sample of retail spaces in similar shopping districts and measures the monthly rent (S) and distance from parking (in yards) for each retail space. This is the same regression you worked with in Worksheet #9. Here is the complete Excel output for this regression: SUMMARY OUTPUT Regression Stotistics Multiple R RSquare 0.7076 0.5007 Adjusted R Square 0.4918 Standard Error 978.8761 Observations 58 ANOVA Significance SS 53809748.97 53809748.97 df MS Regression 56.1572 5.28E-10 Residual 56 53659115.74 958198.4954 Total 57 107468864.7 Coefficients Standard Error t Stat P value Lower 95% Upper 95% 15502.6 8.37 Intercept 15003.10 249.3464 60.17 14E-52 14503.59 Distance -11.42 1.5239 7.49 5.28E-10 -14.47 NOTE: Excel uses scientific notation for very small numbers. So the p-value = 5.28E-10 = 5.28 x 10 10 - 0.000000000528. In the hypothesis test, you may truncate that to 0.000. Very tiny p-values with more than four zeroes after the decimal are often expressed as 0.000 or .000 when they are reported and interpreted.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Worksheet #10 An analyst for a shopping district would like to determine the rent that should be charged for retail spaces depending on how close they are to parking. The analyst takes a random sample of retail spaces in similar shopping districts and measures the monthly rent ($) and distance from parking (in yards) for each retail space. This is the same regression you worked with in Worksheet #9. Here is the complete Excel output for this regression: SUMMARY OUTPUT Regression Stotistics Multiple R R Square 0.7076 0.5007 Adjusted R Square Standard Error 0.4918 978.8761 Observations 58 ANOVA Significaner df SS MS Regression 1 53809748.97 53809748.97 56.1572 5.28E-10 Residual 56 53659115.74 958198.4954 Total 57 107468864.7 Coefficients t Stat P value Upper 95% Standard Error Lower 95% Intercept 15003.10 249.3464 60.17 1.4E-52 14503.59 15502.6 Distance -11.42 1.5239 -7,49 5.28E-10 -14.47 8.37 NOTE: Excel uses scientific notation for very small numbers. So the p-value = 5.28E-10 = 5.28 x 10 10 - 0.000000000528. In the hypothesis test, you may truncate that to 0.000. Very tiny p-values with more than four zeroes after the decimal are often expressed as 0.000 or .000 when they are reported and interpreted.
Transcribed Image Text:Worksheet #10 An analyst for a shopping district would like to determine the rent that should be charged for retail spaces depending on how close they are to parking. The analyst takes a random sample of retail spaces in similar shopping districts and measures the monthly rent ($) and distance from parking (in yards) for each retail space. This is the same regression you worked with in Worksheet #9. Here is the complete Excel output for this regression: SUMMARY OUTPUT Regression Stotistics Multiple R R Square 0.7076 0.5007 Adjusted R Square Standard Error 0.4918 978.8761 Observations 58 ANOVA Significaner df SS MS Regression 1 53809748.97 53809748.97 56.1572 5.28E-10 Residual 56 53659115.74 958198.4954 Total 57 107468864.7 Coefficients t Stat P value Upper 95% Standard Error Lower 95% Intercept 15003.10 249.3464 60.17 1.4E-52 14503.59 15502.6 Distance -11.42 1.5239 -7,49 5.28E-10 -14.47 8.37 NOTE: Excel uses scientific notation for very small numbers. So the p-value = 5.28E-10 = 5.28 x 10 10 - 0.000000000528. In the hypothesis test, you may truncate that to 0.000. Very tiny p-values with more than four zeroes after the decimal are often expressed as 0.000 or .000 when they are reported and interpreted.
1) Following the four steps in Ch 14: Handout N2, perform the hypothesis test to answer this question: Is there a statistically significant relationship between Monthly Rent and Distance from parking? Use an a - 0.115 signilicance level. You can report the appropriatet test statistic from the output table above, but be aware that you could calculate it by hand using tes - h/, You can show the p-value approach only, and just report the p-value from the autput (but the df = n-p-1, same as the SSE, if you want to check the CV approach too :). For the following cuestions, refer to the Regression Output Equations roadmap and the output above. 2) How many observations were in this dataset? (i - number of observations! 31 Identify the SSR, SSE, and SST on the output on page 1. SSR - SSE - SST = Which of these is minimized by the regression procedure, in order to determine the slope and intercept of the regression line?
Transcribed Image Text:1) Following the four steps in Ch 14: Handout N2, perform the hypothesis test to answer this question: Is there a statistically significant relationship between Monthly Rent and Distance from parking? Use an a - 0.115 signilicance level. You can report the appropriatet test statistic from the output table above, but be aware that you could calculate it by hand using tes - h/, You can show the p-value approach only, and just report the p-value from the autput (but the df = n-p-1, same as the SSE, if you want to check the CV approach too :). For the following cuestions, refer to the Regression Output Equations roadmap and the output above. 2) How many observations were in this dataset? (i - number of observations! 31 Identify the SSR, SSE, and SST on the output on page 1. SSR - SSE - SST = Which of these is minimized by the regression procedure, in order to determine the slope and intercept of the regression line?
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