GRE Subject Test: Psychology : Statistical Procedures
Study concepts, example questions & explanations for GRE Subject Test: Psychology
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Example Questions
Example Question #31 : Statistical Procedures
Which of the following is a situation where you might prefer a one-tailed test to a two-tailed test?
None of these
When the sample size is excessively high
When only deviations above a particular score are of research interest
When comparisons between groups are more important then comparisons across groups
When the sample size is excessively low
When only deviations above a particular score are of research interest
A two-tailed test differs from a one-tailed test primarily in that it examines deviations both above and below a particular mean. Thus, a one-tailed test is most appropriate when only one direction of deviation is of relevant interest.
Example Question #32 : Statistical Procedures
Each of the following is true about homoscedasticity except which of the following?
Meeting the assumption of homoscedasticity is necessary to demonstrate an unbiased estimate
It largely determines goodness of fit (as defined by Pearson's r)
None of these
It can be tested by regression of squared residuals
It follows the assumption that standard deviations of the error terms are constant within measures
Meeting the assumption of homoscedasticity is necessary to demonstrate an unbiased estimate
Homoscedasticity is explicitly not required to ensure unbiased, asymptotically normal, or reliable results. They are, however, required to show goodness of fit.
Example Question #33 : Statistical Procedures
When testing for non-groupwise homogeneity of variance, the most sensitive test to departures from normality is generally which of the following?
None of these
Goldfeld-Quandt test
Bartlett's test
Levene's test
Brown-Forsythe test
Bartlett's test
Levene's test and the Brown-Forsythe test for homogeneity of variance are not very sensitive to departures from normality, which makes them more useful as tests for nonstandard data sets but less able to predict goodness of fit. Goldfeld-Quandt is a test for groupwise homogeneity of variance, and is useless for the stated purpose.
Example Question #34 : Statistical Procedures
Dr. Crawford believes she has invented a pill to help with student memorization. For a trial experiment, she gathered two groups of twenty students. She gave the twenty students in Group A the “smart pill”, and the twenty students in Group B a sugar pill. After waiting five minutes, both groups of students were given a list of forty words, and were instructed to memorize the entire list in any order. The students were given five minutes to memorize the list. The students were then asked to verbally recite all of the words they could remember in any order within three minutes.
Group A recited an average of fifteen words, while Group B recited an average of ten words.
Which statistical analysis should Dr. Crawford use?
Cannonical correlation
Chi-square
T-test
Pearson-R
ANOVA
T-test
A t-test is most appropriate when only analyzing two variables. Dr. Crawford is analyzing the means between Group A, who received the smart pill, and Group B, who did not. This test will determine whether the differences in means is due to chance or if there is a statistically sound significant difference.
Example Question #35 : Statistical Procedures
Dr. Crawford believes she has invented a pill to help with student memorization. For a trial experiment, she gathered two groups of twenty students. She gave the twenty students in Group A the “smart pill”, and the twenty students in Group B a sugar pill. After waiting five minutes, both groups of students were given a list of forty words, and were instructed to memorize the entire list in any order. The students were given five minutes to memorize the list. The students were then asked to verbally recite all of the words they could remember in any order within three minutes.
Group A recited an average of fifteen words, while Group B recited an average of ten words.
Dr. Crawford can for sure reject her null hypothesis if she obtains a calculated p-value equal to which of the following?
None of these
The p-value represents the probability that differences in means are due to random chance and not due to the independent variable’s effects. The smaller the p-value, the less likely it is that differences in means are random. This supports the researcher rejecting the null hypothesis; therefore, the following p-value is the correct answer:
Example Question #36 : Statistical Procedures
After much success with her initial experiments (i.e. Groups A and B) and pilot test, Dr. Crawford wanted to further test the effects of a “smart pill." She recruited a new group of twenty students, Group C, for this next experiment. In the first trial, she gave the students the smart pill, and then waited five minutes to give them the list of forty words. Students were instructed to memorize the list in any order and were given five minutes to study it. The students were then asked to verbally recite all of the words they could remember within three minutes. One week later, Dr. Crawford repeated the experiment with the same group and same list of words. However, on the second trial, students were given the sugar pill instead of the smart pill.
On the first trial, students from Group C recalled an average of seventeen words. On the second trial, students recalled an average of twenty words.
Which statistical analysis should Dr. Crawford use?
ANOVA
Chi-square
Cannonical correlation
Pearson-R
T-test
T-test
A t-test is most appropriate when only analyzing two variables. Dr. Crawford is analyzing the means produced by students in Group C, but under two different conditions. This test will determine whether the differences in means is due to chance or if there is a statistically sound significant difference.
Example Question #35 : Statistical Procedures
Which of the following best describes a normal distribution?
Unimodal, asymptotic, and asymmetric
Bimodal, symptotic and asymmetric
Bimodal, asymptotic, and symmetric
Unimodal, asymptotic, and symmetric
None of these
Unimodal, asymptotic, and symmetric
A normal distribution is asymptotic because it approaches a curve closely. It is unimodal because of its singular mode, and it is symmetric because both sides are mirror images of each other. There are other kinds of distributions like skewed distributions that are unimodal, asymptotic, and asymmetrical. These descriptions can vary depending on the shape of the distribution.
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