1) Following the four steps in Ch 14: Handout #2, perform the hypothesis test to answer this question: Is there a statistically significant relationship between Monthly Rent and Distance from parking? Use an a = 0.05 significance level. You can report the appropriate t test statistic from the output table above, but be aware that you could calculate it by hand using ttest = b₁/S₂. You can show the p-value approach only, and just report the p-value from the output (but the df = n-p-1, same as the SSE, if you want to check the CV approach too :). For the following questions, refer to the Regression Output Equations roadmap and the output above. 2) How many observations were in this dataset? (n = number of observations) n = 3) 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? 2
1) Following the four steps in Ch 14: Handout #2, perform the hypothesis test to answer this question: Is there a statistically significant relationship between Monthly Rent and Distance from parking? Use an a = 0.05 significance level. You can report the appropriate t test statistic from the output table above, but be aware that you could calculate it by hand using ttest = b₁/S₂. You can show the p-value approach only, and just report the p-value from the output (but the df = n-p-1, same as the SSE, if you want to check the CV approach too :). For the following questions, refer to the Regression Output Equations roadmap and the output above. 2) How many observations were in this dataset? (n = number of observations) n = 3) 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? 2
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
100%
![1) Following the four steps in Ch 14: Handout #2, perform the hypothesis test to answer this question: Is
there a statistically significant relationship between Monthly Rent and Distance from parking? Use an
a = 0.05 significance level. You can report the appropriate t test statistic from the output table above,
but be aware that you could calculate it by hand using ttest = b₁/S₂. You can show the p-value
approach only, and just report the p-value from the output (but the df=n-p-1, same as the SSE, if
you want to check the CV approach too :).
For the following questions, refer to the Regression Output Equations roadmap and the output above.
2) How many observations were in this dataset? (n = number of observations)
n=
3) 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?
2](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F631d52d2-d8ca-4fc4-a52f-45ccb5125001%2F442d4b55-399d-4485-8f2e-106da23eafa8%2F4b054yn_processed.png&w=3840&q=75)
Transcribed Image Text:1) Following the four steps in Ch 14: Handout #2, perform the hypothesis test to answer this question: Is
there a statistically significant relationship between Monthly Rent and Distance from parking? Use an
a = 0.05 significance level. You can report the appropriate t test statistic from the output table above,
but be aware that you could calculate it by hand using ttest = b₁/S₂. You can show the p-value
approach only, and just report the p-value from the output (but the df=n-p-1, same as the SSE, if
you want to check the CV approach too :).
For the following questions, refer to the Regression Output Equations roadmap and the output above.
2) How many observations were in this dataset? (n = number of observations)
n=
3) 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?
2
![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 ($) and distance from parking (in yards) for
each retail space. This is the same regression you worked with in Worksheet #9.
Here is the complete Excel output for this regression:
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R
Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
Distance
0.7076
0.5007
0.4918
978.8761
58
df
1
56
57
Name:
SS
MS
53809748.97 53809748.97
53659115.74
958198.4954
107468864.7
Coefficients Standard Error
15003.10
-11.42
249.3464
1.5239
t Stat
60.17
-7.49
F
56.1572
P-value
1.4E-52
5.28E-10
Significance
F
5.28E-10
Lower 95%
14503.59
-14.47
Upper 95%
15502.6
-8.37
NOTE: Excel uses scientific notation for very small numbers. So the p-value = 5.28E-10 = 5.28 x 10-10 =
0.000000000528. In the hypothesis test, you may truncate that to 0.000. Very tiny p-values with more
than four zeroes after the decimal are often expressed as 0.000 or .000 when they are reported and
interpreted.
1](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F631d52d2-d8ca-4fc4-a52f-45ccb5125001%2F442d4b55-399d-4485-8f2e-106da23eafa8%2Fzbh9ah_processed.png&w=3840&q=75)
Transcribed Image Text:Worksheet #10
An analyst for a shopping district would like to determine the rent that should be charged for retail
spaces depending on how close they are to parking. The analyst takes a random sample of retail spaces
in similar shopping districts and measures the monthly rent ($) 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 Statistics
Multiple R
R Square
Adjusted R
Square
Standard Error
Observations
ANOVA
Regression
Residual
Total
Intercept
Distance
0.7076
0.5007
0.4918
978.8761
58
df
1
56
57
Name:
SS
MS
53809748.97 53809748.97
53659115.74
958198.4954
107468864.7
Coefficients Standard Error
15003.10
-11.42
249.3464
1.5239
t Stat
60.17
-7.49
F
56.1572
P-value
1.4E-52
5.28E-10
Significance
F
5.28E-10
Lower 95%
14503.59
-14.47
Upper 95%
15502.6
-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
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