Terms in this set (23)
In a hypothesis test, the larger the value for the estimated standard error, the more likely it is that you will reject the null hypothesis.
Which of the following is a fundamental difference between the t statistic and a z-score?
The t statistic uses the sample variance in place of the population variance.
When the sample size is small, the t distribution ________.
is flatter and more spread out than a normal distribution
As the sample size increases, what happens to the critical values for t? (Assume that the alpha level and all other factors remain constant.)
the values decrease
A researcher reports a t statistic with df = 20. Based on this information, how many individuals were in the sample?
A sample of n = 4 individuals is obtained from a population with μ = 80. Which set of sample statistics would produce the most extreme value for t?
M = 88 and s 2 = 8
The size of the estimated standard error is ________.
nversely related to the sample size and directly related to the sample variance
If the sample variance increases, the estimated standard error will also increase.
A sample of n = 15 scores produces a t statistic of t = -2.96. If a researcher is using a regular two-tailed test with α = .01, what decision should be made?
fail to reject the null hypothesis
A sample is selected from a population with μ = 80 and a treatment is administered to the sample. If the sample variance is s 2 = 20, which set of sample characteristics is most likely to result in a significant effect?
M = 88 for a sample of n = 100
The estimated standard error, s M , provides a measure of
how much difference is reasonable to expect between the sample mean and the population mean.
A researcher reports a t statistic with df = 29. This t statistic was computed for a sample of n = 30 scores.
What t values define the critical region for a regular two-tailed test using a sample of n = 25 scores and an alpha level of .05?
t = ±2.064
In a hypothesis test, a t statistic near zero indicates that the sample mean is relatively close to the population mean that is specified in the null hypothesis.
A sample of n = 4 scores has SS = 48. What is the variance for this sample?
The distribution of t statistics tends to be flatter and more spread out than a normal distribution.
A sample of n = 9 scores has a mean of M = 40 and a variance of s 2 = 9. If this sample is being used to test a null hypothesis stating that μ = 43, then what is the t statistic for the sample?
t = -3.00
A sample of n = 25 scores has a mean of M = 46 and a variance of s 2 = 100. What is the estimated standard error for this sample?
The estimated standard error describes the variability for the set of scores and the sample variance describes how accurately the sample mean represents the population mean.
For a two-tailed hypothesis test with α = .05 using a sample of n = 20 scores, the critical values for t would be t = ±2.086.
A sample of n = 25 scores with a sample variance of s 2 = 100 would have an estimated standard error of 4 points.
To compute a t statistic, you must use the sample variance (or standard deviation) to compute the estimated standard error for the sample mean.
A sample of n = 4 scores has SS = 48. What is the estimated standard error for this sample?