In a simple repeated measures design, SSWS refers to the Sum of Squares Within Subjects, which accounts for variability due to differences between individuals in a repeated measures study. This term is commonly defined as:

SSWS = SSTotal - SSBS

Where:

• SSTotal is the total sum of squares, representing overall variability in the data.
• SSBS is the sum of squares between subjects, accounting for variability due to differences between participants.

Thus, the correct choice is:

SSWS = SSTotal - SSBS

Would you like a detailed explanation or further assistance with this concept?

Related Questions:

1. What are the steps to compute SSWS in a repeated measures ANOVA?
2. How does SSWS differ from SSResidual?
3. What is the significance of partitioning variance in repeated measures designs?
4. How do you interpret SSBS and its role in repeated measures?
5. Can SSWS be zero, and under what conditions?

Tip: Always double-check that your sums of squares add up to the total variance to confirm your calculations!