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Essentials of Statistics for the B...

8th Edition
Frederick J Gravetter + 1 other
ISBN: 9781133956570

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BuyFindarrow_forward

Essentials of Statistics for the B...

8th Edition
Frederick J Gravetter + 1 other
ISBN: 9781133956570
Textbook Problem

Masculine-themed words (such us competitive, independent, analyze, strong) are commonly used in job recruitment materials, especially for job advertisements in male-dominated areas (Gaucher, Friesen, & Kay, 2010). The same study found that these words also make the jobs less appealing to women. In a similar study, female participants were asked to read a series of job advertisements and then rate how interesting or appealing the job appeared to be. Half of the advertisements were constructed to include, several masculine-themed words and the others were worded neutrally. The average rating for each type of advertisement was obtained for each participant. For n – 25 participants, the mean difference between the two types of advertisements is MD = 1.32 points (neutral ads rated higher) with SS – 150 for the difference scores.

a. Is this result sufficient to conclude that there is a significant difference in the ratings for two types of advertisements? Use a two-tailed test with α = .05.

b. Compute r2 to measure the size of the treatment effect.

c. Write a sentence describing the outcome of the hypothesis test and the measure of effect size as it would appear in a research report.

a.

To determine

There is a significant difference in the ratings for two types of advertisements.

Explanation

Given info:

Numbers of participants in the sample are n=25 .

Sample mean difference MD=1.32 .

Sum of squares is SS=150 .

Level of significance for two tailed test is α=0.05 .

Calculation:

State the hypotheses:

Null Hypothesis:

H0:μD=0

That is, there is no significant difference in the masculine words advertisement and advertisements.

Alternate Hypothesis:

H1:μD0

That is, there is a significant difference in the ratings for two types of advertisements.

In repeated-measures study, t statistic under null hypothesis is given by:

t=MDμDSS(n1)×n=1

b.

To determine

r2 to measure the size of the treatment effect.

c.

To determine

To Describe: The outcome of the hypothesis test and the measure of the effect size.

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