In the repeated-measures t statistic, the value of the estimated standard error in the denominator is computed entirely from the sample data
In a repeated-measures study comparing two treatments with a sample of n=15 participants, the researcher measures two scores for each individual to obtain a total of 30 scores. The repeated measures t statistic for this study has df=29
False; The 30 scores are used to compute 15 different scores: df=14
If a set of n=16 difference scores has a mean of MD=4 and a variance of s(sqd)=36. Cohen's d for this sample is d=4/6
A repeated measures study with a sample of n=16 participants produces a repeated measures t=2.00. If effect size is measuring using r(sqd), then r(sqd)=4/20.
High variance for a sample of difference scores indicates that the treatment does not have a consistent effect.
If other factors are held constant, the higher the variance is for a sample of difference scores, the lower the likelihood of rejecting the null hypothesis
A repeated measures study would not be appropriate for which situation?
A researcher would like to compare individuals from two different populations. (Two difference populations will require two different samples).
A repeated measures study and a matched subjects study are both used to compare two treatments. If each study uses a total of 30 participants, then what are the df values for the two studies?