(d) Fill in the blanks in the following table. Source of Variation DF Mean Square F Value Sum of Squares SSR = 16059 1 MSR = 16058.9 ? Regression Residual 12 ? = ? SSE = ? MSE=15366 ? (e) (i) Write down the null hypothesis, that there is no effect on mean sales from increasing the amount of shelf space, versus a suitable alternative hypothesis. (ii) Compare the above value of F with the table value F(0.01). (iii) Comment on your findings.
(d) Fill in the blanks in the following table. Source of Variation DF Mean Square F Value Sum of Squares SSR = 16059 1 MSR = 16058.9 ? Regression Residual 12 ? = ? SSE = ? MSE=15366 ? (e) (i) Write down the null hypothesis, that there is no effect on mean sales from increasing the amount of shelf space, versus a suitable alternative hypothesis. (ii) Compare the above value of F with the table value F(0.01). (iii) Comment on your findings.
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
![(d) Fill in the blanks in the following table.
Source of Variation
DF
Mean Square
F Value
Sum of Squares
SSR = 16059
1
MSR
=
16058.9
?
Regression
Residual
15366
12
??
SSE = ?
MSE = =
?
(e) (i) Write down the null hypothesis, that there is no effect on mean sales from
increasing the amount of shelf space, versus a suitable alternative hypothesis.
(ii) Compare the above value of F with the table value Fl(0.01).
(iii) Comment on your findings.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F09bbdd7d-a5f9-436c-973a-78e5eef6493e%2F21666a1a-76e0-4d08-8cc5-5ffecd764473%2Fyd51ry_processed.png&w=3840&q=75)
Transcribed Image Text:(d) Fill in the blanks in the following table.
Source of Variation
DF
Mean Square
F Value
Sum of Squares
SSR = 16059
1
MSR
=
16058.9
?
Regression
Residual
15366
12
??
SSE = ?
MSE = =
?
(e) (i) Write down the null hypothesis, that there is no effect on mean sales from
increasing the amount of shelf space, versus a suitable alternative hypothesis.
(ii) Compare the above value of F with the table value Fl(0.01).
(iii) Comment on your findings.
![A baker is interested to find the relationship between the width of the shelf space for her
brand of cookies (x, in feet) and monthly sales (y) of the product in a supermarket. Hence,
she fits a model relating monthly sales y to the amount of shelf space x her cookies receive
that month. That is, she is fitting the model in the following way
y=B+₂x+e
where ~ N(0,0¹).
x (shelf space) y (weekly sales)
weekly sales VS shelf space
3
2
6
575
5
3
450
8
630
4
435
2
498
6
534
3
530
2
457
7
2
3
5
7
Using R, we obtained the following output.
> mody <- 1m (y - x)
> summary (mody)
Call:
lm (formula y - x)
Residuals:
Min
10 Median
3Q
Max
-67.022 -31.346 -0.631 33.654 54.734
Coefficients:
(Intercept) 429.048
26.519 16.179 1.69e-08 ***
x
18.244
5.643 3.233 0.00898 **
Signif. codes: 0*** 0.001 **0.01 0.05 0.11
Residual standard error: 39.2 on 10 degrees of freedom
Multiple R-squared: 0.511,
Adjusted R-squared: 0.4621
F-statistic: 10.45 on 1 and 10 DF, p-value: 0.008979
> anova (mody)
Analysis of Variance Table
Response: y
X
1
Df Sum Sq Mean Sq F value Pr (>F)
16059 16058.9 10.451 0.008979 **
Residuals 10 15366 1536.6
Signif. codes: 0 '*** 0.001 '**' 0.01 0.05. 0.11
8
4
Estimate Std. Error t value Pr(>|t|)
.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F09bbdd7d-a5f9-436c-973a-78e5eef6493e%2F21666a1a-76e0-4d08-8cc5-5ffecd764473%2Fyr8pyyb_processed.png&w=3840&q=75)
Transcribed Image Text:A baker is interested to find the relationship between the width of the shelf space for her
brand of cookies (x, in feet) and monthly sales (y) of the product in a supermarket. Hence,
she fits a model relating monthly sales y to the amount of shelf space x her cookies receive
that month. That is, she is fitting the model in the following way
y=B+₂x+e
where ~ N(0,0¹).
x (shelf space) y (weekly sales)
weekly sales VS shelf space
3
2
6
575
5
3
450
8
630
4
435
2
498
6
534
3
530
2
457
7
2
3
5
7
Using R, we obtained the following output.
> mody <- 1m (y - x)
> summary (mody)
Call:
lm (formula y - x)
Residuals:
Min
10 Median
3Q
Max
-67.022 -31.346 -0.631 33.654 54.734
Coefficients:
(Intercept) 429.048
26.519 16.179 1.69e-08 ***
x
18.244
5.643 3.233 0.00898 **
Signif. codes: 0*** 0.001 **0.01 0.05 0.11
Residual standard error: 39.2 on 10 degrees of freedom
Multiple R-squared: 0.511,
Adjusted R-squared: 0.4621
F-statistic: 10.45 on 1 and 10 DF, p-value: 0.008979
> anova (mody)
Analysis of Variance Table
Response: y
X
1
Df Sum Sq Mean Sq F value Pr (>F)
16059 16058.9 10.451 0.008979 **
Residuals 10 15366 1536.6
Signif. codes: 0 '*** 0.001 '**' 0.01 0.05. 0.11
8
4
Estimate Std. Error t value Pr(>|t|)
.
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