b. Based on your answer to Part (a), write a few sen- tences commenting on the theory that the more re- strictive the age label on a video game, the more at- tractive the game is to 12- to 13-year-old boys. 15.18 The paper referenced in Exercise 15.5 de- scribed an experiment to determine if restrictive age la- beling on video games increased the attractiveness of the game for boys age 12 to 13. In that exercise, the null hypothesis of Ho: ₁ = μ₂ = μ3 = μ4, where μ₁ is the population mean attractiveness rating for the game with the 7+ age label, and M2, M3, and M4 are the population mean attractiveness scores for the 12+, 16+, and 18+ age labels, respectively. The sample data is given in the accompanying table. 7+ label 12+ label 16+ label 18+ label 6 8 7 10 6 7 9 9 6 8 8 6 5 5 6 8 7 7 7 8 9 4 6 5 8 8 1 8 9 9 2 4 6 10 4 7 7 8 a. Compute the 95% T-K intervals and then use the underscoring procedure described in this section to identify significant differences among the age labels.
b. Based on your answer to Part (a), write a few sen- tences commenting on the theory that the more re- strictive the age label on a video game, the more at- tractive the game is to 12- to 13-year-old boys. 15.18 The paper referenced in Exercise 15.5 de- scribed an experiment to determine if restrictive age la- beling on video games increased the attractiveness of the game for boys age 12 to 13. In that exercise, the null hypothesis of Ho: ₁ = μ₂ = μ3 = μ4, where μ₁ is the population mean attractiveness rating for the game with the 7+ age label, and M2, M3, and M4 are the population mean attractiveness scores for the 12+, 16+, and 18+ age labels, respectively. The sample data is given in the accompanying table. 7+ label 12+ label 16+ label 18+ label 6 8 7 10 6 7 9 9 6 8 8 6 5 5 6 8 7 7 7 8 9 4 6 5 8 8 1 8 9 9 2 4 6 10 4 7 7 8 a. Compute the 95% T-K intervals and then use the underscoring procedure described in this section to identify significant differences among the age labels.
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
![b. Based on your answer to Part (a), write a few sen-
tences commenting on the theory that the more re-
strictive the age label on a video game, the more at-
tractive the game is to 12- to 13-year-old boys.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbd1e3813-29ee-4559-9532-7c63fe4cc8e7%2Fa16b1801-029c-4801-b80c-3a3629007c05%2Fyuurdtph_processed.png&w=3840&q=75)
Transcribed Image Text:b. Based on your answer to Part (a), write a few sen-
tences commenting on the theory that the more re-
strictive the age label on a video game, the more at-
tractive the game is to 12- to 13-year-old boys.
![15.18 The paper referenced in Exercise 15.5 de-
scribed an experiment to determine if restrictive age la-
beling on video games increased the attractiveness of the
game for boys age 12 to 13. In that exercise, the null
hypothesis of Ho: ₁ = μ₂ = μ3 = μ4, where μ₁ is the
population mean attractiveness rating for the game with
the 7+ age label, and M2, M3, and M4 are the population
mean attractiveness scores for the 12+, 16+, and 18+
age labels, respectively. The sample data is given in the
accompanying table.
7+ label 12+ label
16+ label
18+ label
6
8
7
10
6
7
9
9
6
8
8
6
5
5
6
8
7
7
7
8
9
4
6
5
8
8
1
8
9
9
2
4
6
10
4
7
7
8
a. Compute the 95% T-K intervals and then use the
underscoring procedure described in this section to
identify significant differences among the age labels.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbd1e3813-29ee-4559-9532-7c63fe4cc8e7%2Fa16b1801-029c-4801-b80c-3a3629007c05%2Ft372g8k_processed.png&w=3840&q=75)
Transcribed Image Text:15.18 The paper referenced in Exercise 15.5 de-
scribed an experiment to determine if restrictive age la-
beling on video games increased the attractiveness of the
game for boys age 12 to 13. In that exercise, the null
hypothesis of Ho: ₁ = μ₂ = μ3 = μ4, where μ₁ is the
population mean attractiveness rating for the game with
the 7+ age label, and M2, M3, and M4 are the population
mean attractiveness scores for the 12+, 16+, and 18+
age labels, respectively. The sample data is given in the
accompanying table.
7+ label 12+ label
16+ label
18+ label
6
8
7
10
6
7
9
9
6
8
8
6
5
5
6
8
7
7
7
8
9
4
6
5
8
8
1
8
9
9
2
4
6
10
4
7
7
8
a. Compute the 95% T-K intervals and then use the
underscoring procedure described in this section to
identify significant differences among the age labels.
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