Ch. 9 Quiz 9 (PSYC 2013, NWACC)
Q: If a researcher is using a t statistic to test a null hypothesis about a population, what information is needed from the population to calculate the t statistic?
The t statistic does not require any information about the population.
Q: Under what circumstances can a very small treatment effect be statistically significant?
If the sample size big and the sample variance is small
Q: On average, what value is expected for the t statistic when the null hypothesis is true?
0
Q: If other factors are held constant, how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r2 and Cohen's d?
A larger sample increases the likelihood but has little influence on measures of effect size.
Q: A hypothesis test produces a t statistic of t = 2.20. If the researcher is using a two-tailed test with a = .05, how large does the sample have to be in order to reject the null hypothesis?
At least n = 13
T/F: As the sample size is increased, the distribution of t statistics becomes flatter and more spread out.
False
T/F: If the null hypothesis states that m = 70 and a researcher obtains a sample with M = 73 and s2 = 9, then Cohen's d = 0.33.
False
T/F: In general, the larger the value of the sample variance, the greater the likelihood of rejecting the null hypothesis.
False
Q: The results of a hypothesis test are reported as follows: t(15) = 2.70, p < .05. Based on this report, how many individuals were in the sample?
16
Q: Which of the following would have no effect on the width of a confidence interval?
Increase the sample mean
Q: Which combination of factors would definitely increase the width of a confidence interval?
Increase the sample mean and increase the percentage of confidence
Q: A sample has a mean of M = 39.5 and a standard deviation of s = 4.3, and produces a t statistic of t = 2.14. For a two-tailed hypothesis test with a = .05, what is the correct statistical decision for this sample?
It is impossible to make a decision about H0 without more information.
Q: Which of the following describes what a confidence interval does?
It uses a sample mean to estimate the corresponding population mean.
Q: How does sample variance influence the estimated standard error and measures of effect size such as r2 and Cohen's d?
Larger variance increases the standard error but decreases measures of effect size.
Q: If other factors are held constant, which set of sample characteristics is most likely to reject a null hypothesis stating that m = 80?
M = 90 for a sample of n = 100
Q: A hypothesis test with a sample of n = 25 participants produces a t statistic of t = +2.53. Assuming a one-tailed test with the critical region in the right-hand tail, what is the correct decision?
The researcher can reject the null hypothesis with either a = .05 or a = .01.
Q: A sample of n = 25 scores produces a t statistic of t = -2.062. If the researcher is using a two-tailed test, which of the following is the correct statistical decision?
The researcher must fail to reject the null hypothesis with either a = .05 or a = .01.
Q: 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.
T/F: A research report states "t(15) = 2.31, p < .05." For this study, the sample had n = 16 scores.
True
T/F: A sample of n = 4 scores with SS = 48 has a variance of 16 and an estimated standard error of 2.
True
T/F: As sample size increases, the critical region boundaries for a two-tailed test with a = .05 will move closer to zero.
True
T/F: Compared to a z-score, a hypothesis test with a t statistic requires less information from the population.
True
T/F: Compared to a z-score, a hypothesis test with a t statistic requires more information from the sample.
True
T/F: If a hypothesis test using a sample of n = 16 scores produces a t statistic of t = 2.15, then the correct decision is to reject the null hypothesis for a two-tailed test with a = .05.
True
T/F: If the 90% confidence interval for m is from 40 to 50, then the sample mean is M = 45.
True
T/F: If two samples, each with n = 20 scores, are selected from the same population and both have the same mean (M = 53) and the same variance (s2 = 12), then they will also have the same t statistic.
True
T/F: The sample mean will always be exactly in the center of a confidence interval that is estimating the value of the population mean.
True
T/F: The t distribution for df = 4 is flatter and more spread out than the t distribution for df = 20.
True
T/F: When the population variance or standard deviation is not known, you must use a t statistic instead of a z-score for a hypothesis test.
True
Q: Which of the following samples will have the smallest value for the estimated standard error?
n = 16 with s2 = 16
Q: A researcher conducts a hypothesis test using a sample from an unknown population. If the t statistic has df = 30, how many individuals were in the sample?
n = 31
Q: A sample of n = 16 scores has a mean of M = 65 and an estimated standard error of 2 points. What is the sample variance?
s2= 64
Q: Which set of characteristics will produce the smallest value for the estimated standard error?
A large sample size and a small sample variance
T/F: A sample of n = 16 scores with a sample variance of s2 = 64 has an estimated standard error of 4 points.
False
Q: Two samples from the same population both have M = 84 and s2 = 20, but one sample has n = 10 and the other has n = 20 scores. Both samples are used to evaluate a hypothesis stating that m = 80 and to compute Cohen's d. How will the outcomes for the two samples compare?
The larger sample is more likely to reject the hypothesis, but the two samples will have the same value for Cohen's d.