Answer:
This is an example of a between-subjects factorial design.
Explanation:
In a between-subjects factorial design, all of the independent variables are manipulated between subjects.
Answer:
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The One-Way ANOVA test represents the best choice if one wants to compare the average number of adjustments made by service representatives at five different locations within a region.
The null hypothesis, which claims that samples from populations with the same mean values are used to create all of the groups' samples, is tested by the ANOVA.
The population variance is estimated twice to accomplish this. Numerous assumptions underlie these estimations. An F-statistic is generated by the ANOVA and represents the proportion of variation within the samples to variance estimated among the means.
According to the central limit theorem, the variance of the group means should be less than the variance of the samples if the group means are taken from populations with similar mean values. A larger ratio suggests that samples were taken from populations with different mean values, which is implied by a higher ratio.
To learn more about the One-Way ANOVA test refer to:
brainly.com/question/23638404
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