The manager of Shoprite conducted a study in five of his stores around Polokwane about the packaging of food product. He collected the information over five weeks in the five different stores. Therefore, a Latin-square design model was suggested to be the best model that can be fitted to compare five types of packaging for the food product, in five stores, over a five-week period. The experiment is set up so that each package appears once at each store, and once over each of the five weeks. a) b) c) Week 1 2345 5 1 100 A 140 B 60 C 110 D 90 E 2 120 B 150 C 40 120 E 70 A Store 3 110 C 160 50 E 130 80 B 4 90 D 145 E 70 90 110 C 5 80 E 155 30 100 C 100 D Analyse the data and draw conclusions. Analyse the problem without blocking by weeks and draw conclusion. Perform analysis of the residuals in terms of underlying assumptions of normality, homogenous variance and outliers for the model fitted in part b).
The manager of Shoprite conducted a study in five of his stores around Polokwane about the packaging of food product. He collected the information over five weeks in the five different stores. Therefore, a Latin-square design model was suggested to be the best model that can be fitted to compare five types of packaging for the food product, in five stores, over a five-week period. The experiment is set up so that each package appears once at each store, and once over each of the five weeks. a) b) c) Week 1 2345 5 1 100 A 140 B 60 C 110 D 90 E 2 120 B 150 C 40 120 E 70 A Store 3 110 C 160 50 E 130 80 B 4 90 D 145 E 70 90 110 C 5 80 E 155 30 100 C 100 D Analyse the data and draw conclusions. Analyse the problem without blocking by weeks and draw conclusion. Perform analysis of the residuals in terms of underlying assumptions of normality, homogenous variance and outliers for the model fitted in part b).
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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DESIGN AND ANALYSIS OF EXPERIMENTS

Transcribed Image Text:The manager of Shoprite conducted a study in five of his stores around Polokwane
about the packaging of food product. He collected the information over five weeks in
the five different stores. Therefore, a Latin-square design model was suggested to be
the best model that can be fitted to compare five types of packaging for the food
product, in five stores, over a five-week period. The experiment is set up so that each
package appears once at each store, and once over each of the five weeks.
a)
b)
c)
Week
1
2
3
4
5
1
100 A
140 B
60 C
110 D
90 E
2
120 B
150 C
40
120 E
70 A
Store
3
110 C
160
50 E
130
80 B
4
90 D
145 E
70
90
110 C
5
80 E
155
30
100 C
100 D
Analyse the data and draw conclusions.
Analyse the problem without blocking by weeks and draw conclusion.
Perform analysis of the residuals in terms of underlying assumptions of normality,
homogenous variance and outliers for the model fitted in part b).
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VIEWStep 4: Analyse the data and draw conclusions.
VIEWStep 5: Construct the table and determine the sum of square using table output.
VIEWStep 6: Determine the mean square, F statistics and ANOVA table.
VIEWStep 7: Analyse the ANOVA table and draw conclusions.
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