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A mail-order catalog firm designed a factorial experiment to test the effect of the size of a magazine advertisement and the advertisement design on the number of catalog requests received (data in thousands). Three advertising designs and two different-size advertisements were considered. The data obtained follow.
Size of Advertisement | |||
---|---|---|---|
Small | Large | ||
Design | A | 8 | 12 |
12 | 8 | ||
B | 24 | 24 | |
16 | 28 | ||
C | 8 | 20 | |
16 | 16 |
Use the ANOVA procedure for factorial designs to test for any significant effects due to type of design, size of advertisement, or interaction. Use α = 0.05.
Find the value of the test statistic for type of design.
Find the p-value for type of design. (Round your answer to three decimal places.)
p-value =
State your conclusion about type of design.
Because the p-value ≤ α = 0.05, type of design is not significant.Because the p-value > α = 0.05, type of design is significant. Because the p-value > α = 0.05, type of design is not significant.Because the p-value ≤ α = 0.05, type of design is significant.
Find the value of the test statistic for size of advertisement.
Find the p-value for size of advertisement. (Round your answer to three decimal places.)
p-value =
State your conclusion about size of advertisement.
Because the p-value > α = 0.05, size of advertisement is not significant.Because the p-value > α = 0.05, size of advertisement is significant. Because the p-value ≤ α = 0.05, size of advertisement is significant.Because the p-value ≤ α = 0.05, size of advertisement is not significant.
Find the value of the test statistic for interaction between type of design and size of advertisement.
Find the p-value for interaction between type of design and size of advertisement. (Round your answer to three decimal places.)
p-value =
State your conclusion about interaction between type of design and size of advertisement.
Because the p-value ≤ α = 0.05, interaction between type of design and size of advertisement is significant.
Because the p-value > α = 0.05, interaction between type of design and size of advertisement is significant.
Because the p-value ≤ α = 0.05, interaction between type of design and size of advertisement is not significant.
Because the p-value > α = 0.05, interaction between type of design and size of advertisement is not significant.
Two factor ANOVA | |||||
Size of Advertisement | |||||
Means: | |||||
Small | Large | ||||
A | 10.0 | 10.0 | 10.0 | ||
Design | C | 20.0 | 26.0 | 23.0 | |
B | 12.0 | 18.0 | 15.0 | ||
14.0 | 18.0 | 16.0 | |||
2 | replications per cell | ||||
ANOVA table | |||||
Source | SS | df | MS | F | p-value |
Design | 344.00 | 2 | 172.000 | 10.75 | .010 |
Size of Advertisement | 48.00 | 1 | 48.000 | 3.00 | .134 |
Interaction | 24.00 | 2 | 12.000 | 0.75 | .512 |
Error | 96.00 | 6 | 16.000 | ||
Total | 512.00 | 11 |
(a) Design:
Test statistic = 10.75
p- value = 0.010
Since 0.010 < 0.05, Design is significant
(b) Size of Advertisement:
Test statistic = 3.00
p- value = 0.134
Since 0.134 > 0.05, Size of Advertisement is not significant
(c) Interaction:
Test statistic = 0.75
p- value = 0.512
Since 0.512 > 0.05, there is no significant interaction.
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