Which of the following are assumptions underlying repeated-measures ANOVA? Check all that apply. The population variances for each of the treatment groups (cells) are not equal. The values of the repeated variables are constant. The population variances for each of the groups (cells) are equal. The correlations among the pairs of levels of the repeated variable are constant.
Inverse Normal Distribution
The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.
Mean, Median, Mode
It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.
Z-Scores
A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.
![**Understanding Assumptions in Repeated-Measures ANOVA**
When conducting a repeated-measures analysis of variance (ANOVA), certain assumptions must be met to ensure valid results. Consider the following statements to determine which are the correct assumptions underlying this statistical method. Check all that apply:
- [ ] The population variances for each of the treatment groups (cells) are not equal.
- [ ] The values of the repeated variables are constant.
- [ ] The population variances for each of the groups (cells) are equal.
- [ ] The correlations among the pairs of levels of the repeated variable are constant.
In repeated-measures ANOVA, it's crucial to test for sphericity, which relates to the last statement about correlations. Understanding these assumptions will help in interpreting the ANOVA results accurately.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F13da617e-b4a7-4f19-b16e-f4527c895b06%2F4e05f779-2fee-4ba3-9b5d-8b23d524208a%2Fxdyo5xs_processed.png&w=3840&q=75)
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