Which of the following is the correct null hypothesis for a repeated-measures t test?
A researcher plans to conduct a research study comparing two treatment conditions with a total of 20 participants. Which of the following designs would produce 20 scores in each treatment?
The following data were obtained from a repeated-measures research study. What is the value of MD for these data?
A researcher is using a repeated-measures study to evaluate the difference between two treatments. If the difference between the treatments is consistent from one participant to another, then the data should produce .
For which of the following situations would a repeated-measures research design be appropriate?
A repeated-measures study using a sample of n = 20 participants would produce a t statistic with df = .
A researcher obtains t = 2.25 for a repeated-measures study using a sample of n = 10 participants. Based on this t value, what is the correct decision for a two-tailed test?
Which of the following possibilities is a serious concern with a repeated-measures study?
A repeated-measures study comparing two treatments with n = 4 participants produces MD = 2 and SS = 75 for the difference scores. What is the estimated standard error for the sample mean difference?
If all participants in a repeated-measures study show roughly the same 10-point difference between treatments, then the data are likely to produce a significant value for the t statistic.
Repeated-measures designs are particularly well-suited to research studies examining
For a repeated-measures study, as the sample mean difference increases, the likelihood of rejecting the null hypothesis also increases.
A repeated-measures research study comparing two treatments with a set of 10 scores in each treatment will produce a t statistic with df = 18.
For a repeated-measures study, if other factors are held constant, then an increase in the sample size will increase the likelihood of finding a significant treatment effect.
A repeated-measures test usually is more likely to detect a real treatment effect than an independent-measures test because the repeated-measures design typically has a smaller variance and a smaller estimated standard error.