A regression model relating , number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where total = 40. ANOVA 63.70 Regression Residual Total 10.25 Intercept Number of Salespersons we reject df Coefficients 76.0 43.0 SS 6,404.5 8,931.6 a. Write the estimated regression equation (to whole number). 76 + 43 C b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) MS F F-value p-value is less than 0.01 we reject Ho c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) t Stat p-value is less than 0.01 Ho ₁ 0.0001 d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons. $ thousand (to whole number) Standard Error 10.483 5.506 Significance F t Stat P-value
A regression model relating , number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where total = 40. ANOVA 63.70 Regression Residual Total 10.25 Intercept Number of Salespersons we reject df Coefficients 76.0 43.0 SS 6,404.5 8,931.6 a. Write the estimated regression equation (to whole number). 76 + 43 C b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) MS F F-value p-value is less than 0.01 we reject Ho c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals) t Stat p-value is less than 0.01 Ho ₁ 0.0001 d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons. $ thousand (to whole number) Standard Error 10.483 5.506 Significance F t Stat P-value
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
![A regression model relating , number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where total = 40.
+
63.70
x
ANOVA
Regression
Residual
Total
Intercept
Number of
Salespersons
we reject
df
Coefficients
76.0
43.0
a. Write the estimated regression equation (to whole number).
ŷ =
✔
76
43
b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)
t Stat
p-value is less than 0.01
Ho ₁ 0.0001
d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons.
$
thousand (to whole number)
SS
6,404.5
8,931.6
F-value
p-value is less than 0.01
we reject
Но
c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)
10.25 X
MS F
×
Standard Error
10.483
5.506
Significance F
t Stat
P-value](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc7ca3657-c4f3-48a9-a97f-aeb3b49a42a7%2F149df3d0-27a0-4244-829e-80c0f2775547%2Fkemk6e_processed.png&w=3840&q=75)
Transcribed Image Text:A regression model relating , number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following regression output. Where total = 40.
+
63.70
x
ANOVA
Regression
Residual
Total
Intercept
Number of
Salespersons
we reject
df
Coefficients
76.0
43.0
a. Write the estimated regression equation (to whole number).
ŷ =
✔
76
43
b. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)
t Stat
p-value is less than 0.01
Ho ₁ 0.0001
d. Predict the annual sales at the Memphis branch office. This branch employs 11 salespersons.
$
thousand (to whole number)
SS
6,404.5
8,931.6
F-value
p-value is less than 0.01
we reject
Но
c. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)
10.25 X
MS F
×
Standard Error
10.483
5.506
Significance F
t Stat
P-value
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