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.

Name: Can I have all 3 questions done, Thank you. Worksheet #10An analyst fo
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Description: Can I have all 3 questions done, Thank you. Worksheet #10An analyst for a shopping district would like to determine the rent that should be charged for retailspaces depending on how close they are to parking. The analyst takes a random sample of reta

MATLAB: An Introduction with Applications

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Can I have all 3 questions done, Thank you.

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?

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