Which of the following is a major difference between a hypothesis test with the t statistic formula and the test with a z-score?
You must calculate the sample variance (or standard deviation) for the t statistic but not for the z-score. You use the unit normal table to find critical values for the z-score test but not for the t test. You must know the population variance (or standard deviation) for the z-score but not for the t statistic.
On average, what value is expected for the t statistic when the null hypothesis is true?
What is measured by the estimated standard error, sM?
How much difference is reasonable to expect between a sample mean and the population mean
A sample of n = 25 individuals is selected from a population with µ= 80, and a treatment is administered to the sample. Which set of sample characteristics is most likely to lead to a decision that there is a significant treatment effect?
M = 90 and small sample variance
What is the sample variance and the estimated standard error for a sample of n = 4 scores with SS = 300
s2 = 100 and sM = 5
With α= .01, what is the critical t value for a one-tailed test with n = 30
t = 2.462
A sample has a mean of M = 39.5 and a standard deviation of s = 4.3. In a two-tailed hypothesis test with α= .05, this sample produces a t statistic of t = 2.14. Based on this information, the correct statistical decision is
It is impossible to make a decision about H0 without more information.
A sample of n = 25 scores produces a t statistic of t = -2.05. If the researcher is using a two-tailed test with α = .05, the correct statistical decision is
he researcher must fail to reject the null hypothesis with either α = .05 or α = .01
The results of a hypothesis test are reported as follows: t(29) = 2.70, p < .05. Based on this report, how many individuals were in the sample?
As sample variance increases, what happens to measures of effect size such as r2 and Cohen's d