In 2018, a consumer goods giant had more than 20 brands with more than $1 billion in annual sales. How does the company create so many successful consumer products? They effectively invests in research and development to understand what consumers want. One method used to determine consumer preferences is called conjoint analysis. Conjoint analysis allows a company to ascertain the utility that a respondent in the conjoint study places on a design of a given product. The higher the utility, the more valuable a respondent finds the design. Suppose we have conducted a conjoint study and have the following estimated utilities (higher is preferred) for each of three different designs for a new whitening toothpaste. Respondent Utilities Design A Design B Design C 1 24.6 34.4 28.8 2 31.4 31.4 33.9 3 31.8 20.2 27.8 4 15.4 26.4 25.1 5 20.7 18.3 18.2 6 41.0 34.0 44.8 7 27.1 22.5 27.3 8 20.2 21.8 27.9 9 31.6 29.4 31.3 10 24.4 29.0 29.3 At the 0.05 level of significance, test for any significant differences. State the null and alternative hypotheses. H0: At least two of the population means are equal. Ha: At least two of the population means are different. H0: Not all the population means are equal. Ha: ?Design A = ?Design B = ?Design C H0: ?Design A ≠ ?Design B ≠ ?Design C Ha: ?Design A = ?Design B = ?Design C H0: ?Design A = ?Design B = ?Design C Ha: ?Design A ≠ ?Design B ≠ ?Design C H0: ?Design A = ?Design B = ?Design C Ha: Not all the population means are equal. Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value = State your conclusion. Reject H0. There is sufficient evidence to conclude that there is a difference in design. Do not reject H0. There is sufficient evidence to conclude that there is a difference in design. Reject H0. There is not sufficient evidence to conclude that there is a difference in design. Do not reject H0. There is not sufficient evidence to conclude that there is a difference in design.

In 2018, a consumer goods giant had more than 20 brands with more than $1 billion in annual sales. How does the company create so many successful consumer products? They effectively invests in research and development to understand what consumers want. One method used to determine consumer preferences is called conjoint analysis. Conjoint analysis allows a company to ascertain the utility that a respondent in the conjoint study places on a design of a given product. The higher the utility, the more valuable a respondent finds the design. Suppose we have conducted a conjoint study and have the following estimated utilities (higher is preferred) for each of three different designs for a new whitening toothpaste. Respondent Utilities Design A Design B Design C 1 24.6 34.4 28.8 2 31.4 31.4 33.9 3 31.8 20.2 27.8 4 15.4 26.4 25.1 5 20.7 18.3 18.2 6 41.0 34.0 44.8 7 27.1 22.5 27.3 8 20.2 21.8 27.9 9 31.6 29.4 31.3 10 24.4 29.0 29.3 At the 0.05 level of significance, test for any significant differences. State the null and alternative hypotheses. H0: At least two of the population means are equal. Ha: At least two of the population means are different. H0: Not all the population means are equal. Ha: ?Design A = ?Design B = ?Design C H0: ?Design A ≠ ?Design B ≠ ?Design C Ha: ?Design A = ?Design B = ?Design C H0: ?Design A = ?Design B = ?Design C Ha: ?Design A ≠ ?Design B ≠ ?Design C H0: ?Design A = ?Design B = ?Design C Ha: Not all the population means are equal. Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value = State your conclusion. Reject H0. There is sufficient evidence to conclude that there is a difference in design. Do not reject H0. There is sufficient evidence to conclude that there is a difference in design. Reject H0. There is not sufficient evidence to conclude that there is a difference in design. Do not reject H0. There is not sufficient evidence to conclude that there is a difference in design.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Related questions

Question

Respondent	Utilities
Design A	Design B	Design C
1	24.6	34.4	28.8
2	31.4	31.4	33.9
3	31.8	20.2	27.8
4	15.4	26.4	25.1
5	20.7	18.3	18.2
6	41.0	34.0	44.8
7	27.1	22.5	27.3
8	20.2	21.8	27.9
9	31.6	29.4	31.3
10	24.4	29.0	29.3

At the 0.05 level of significance, test for any significant differences.

State the null and alternative hypotheses.

H₀: At least two of the population means are equal.
H_a: At least two of the population means are different. H₀: Not all the population means are equal.
H_a: ?_{Design A} = ?_{Design B} = ?_{Design C} H₀: ?_{Design A} ≠ ?_{Design B} ≠ ?_{Design C}
H_a: ?_{Design A} = ?_{Design B} = ?_{Design C} H₀: ?_{Design A} = ?_{Design B} = ?_{Design C}
H_a: ?_{Design A} ≠ ?_{Design B} ≠ ?_{Design C} H₀: ?_{Design A} = ?_{Design B} = ?_{Design C}
H_a: Not all the population means are equal.

Find the value of the test statistic. (Round your answer to two decimal places.)

Find the p-value. (Round your answer to three decimal places.)

p-value =

State your conclusion.

Reject H₀. There is sufficient evidence to conclude that there is a difference in design. Do not reject H₀. There is sufficient evidence to conclude that there is a difference in design. Reject H₀. There is not sufficient evidence to conclude that there is a difference in design. Do not reject H₀. There is not sufficient evidence to conclude that there is a difference in design.

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