Question 1

The post-hoc test which holds the familywise error rate at .05 by running each individual test at the c/alpha level (# comparisons/alpha) is the
A) Fisher's LSD.
B) Bonferroni.
C) Newmann Keuls.
D) Tukey test.

Accepted Answer

The Bonferroni correction is the most appropriate choice because it controls the familywise error rate at a desired level by adjusting the alpha level for each individual test based on the number of comparisons being made. This ensures that the overall probability of making at least one Type I error across all tests does not exceed the desired level. Fisher's LSD test, Newman Keuls test, and Tukey test do not control the familywise error rate in the same way as the Bonferroni correction.

Question 2

What are our choices for effect size measures for a one-way ANOVA? A) B) η² C) w ² D) all of the above

Accepted Answer

The answer of What are our choices for effect size...

Question 3

When looking at multiple comparisons, the more tests that you run, the more likely that you will have a _______.
A) Type I error
B) Type II error
C) mean squared error
D) random error

Accepted Answer

The more tests that are run, the greater the chance of finding a significant difference by chance alone. This increases the likelihood of making a Type I error, which is rejecting the null hypothesis when it is actually true.

Question 4

You want to control the _______ when multiple comparisons are being made?
A) probability error rate
B) significance error rate
C) familywise error rate
D) test-retest error rate

Accepted Answer

When making multiple comparisons, it is important to control the familywise error rate to minimize the chance of making a Type I error (rejecting a true null hypothesis). The familywise error rate controls the overall probability of making at least one Type I error. Options A and B are similar concepts but do not specifically address the issue of multiple comparisons. Option D is not related to the issue of multiple comparisons.

Question 5

Which of the following is not a multiple comparison procedure we have discussed in class or seen in the texts.
A) Fisher's LSD test.
B) The Stroop test.
C) The Bonferroni test.
D) The Newman-Keuls test.

Accepted Answer

The Stroop test is not a multiple comparison procedure; it is a cognitive psychology test used to measure a person's selective attention and cognitive flexibility. The other three choices (Fisher's LSD test, Bonferroni test, and Newman-Keuls test) are all multiple comparison procedures used to control for the increased risk of Type I error when making multiple comparisons in statistical analyses.

Question 6

The null hypothesis behind a simple multiple-group analysis of variance is of the form:
A) 
B) 
C) 
D)

Accepted Answer

The null hypothesis behind a simple multiple-group analysis of variance is that the means of all groups are equal. Choice C represents this null hypothesis in symbolic form: H0: μ1 = μ2 = μ3 = ... = μk, where μ represents the population mean of each group and k represents the number of groups being compared.

Question 7

Eysenck's study on recall as a function of level of processing showed
A) processing makes only minimal difference to recall.
B) old people don't learn anything.
C) just telling someone to learn a list of words doesn't work.
D) recall increases with the level of processing.

Accepted Answer

Eysenck's study found that recall increased as the level of processing increased, indicating that deeper processing leads to better memory retention.

Question 8

A common criticism of Fisher's LSD test is that
A) it is sometimes too conservative.
B) it is sometimes too liberal.
C) it is too difficult.
D) it relies on a non-normal distribution.

Accepted Answer

Fisher's LSD (Least Significant Difference) test is often criticized for being too liberal, meaning it has a higher chance of committing Type I errors (incorrectly rejecting a true null hypothesis) compared to more conservative post-hoc tests. This is because it does not adjust for the increased risk of these errors when multiple comparisons are made.

Question 9

In the analysis of variance, MS_Groups measures how different group means are, and MS_error measures variability within each group. If the null hypothesis were false, what would we expect to find? A) That MS_groups and MS_error would be roughly equal. B) That MS_groups would be larger than MS_error. C) That MS_error is larger than MS_groups. D) That MS_error is close to zero.

Accepted Answer

If the null hypothesis were false, we would expect to find that there is a significant difference between group means. Therefore, the MS_groups measure would be larger than the MS_error measure, indicating that the variability between groups is larger than the variability within groups.

Question 10

The familywise error rate is
A) the probability of at least one Type I error in a set of comparisons.
B) the probability of no Type I errors.
C) the number of Type I errors that you are likely to make.
D) the probability of a Type II error.

Accepted Answer

The familywise error rate is defined as the probability of at least one Type I error in a set of comparisons. It's a way to control the overall probability of making a Type I error when conducting multiple statistical tests or comparisons.

Question 11

A researcher found significant differences in the mean running speeds of sprinters wearing shoes made by Nike, Reebok, and Adidas using an analysis of variance. The η² calculated on the basis of group membership (based on which shoes were worn) equaled .16. The value of η² shows that A) the r value would be .4. B) 84% of the variability in running speed is attributed to shoe brand. C) 16% of the variability in running speed is attributed to shoe brand. D) most of the factors influencing running speed are contained in the brand of shoes worn by runners.

Accepted Answer

The value of η² is the proportion of total variance in the dependent variable (running speed) that is accounted for by the independent variable (shoe brand). Therefore, a value of .16 means that 16% of the variability in running speed is attributed to the brand of shoes worn by the sprinters.

Question 12

We want to compare the scores of different groups on a measure of reaction time. Three different groups were studied: patients with recent head injuries, patients with old head injuries, and a control group of non-injured people. We want to know which group of people has the fastest reaction time. What is the best statistical test to use to find this out?
A) one-way ANOVA
B) factorial ANOVA
C) paired samples t -test
D) correlation

Accepted Answer

One-way ANOVA is appropriate for comparing the means of three or more independent groups on a continuous variable, in this case, the reaction time. It will identify if there are significant differences between the groups, and if so, which group(s) differ from the others. Factorial ANOVA would be used if there were additional factors being considered, such as age or gender. Paired samples t-test is used when comparing the means of two dependent groups, which is not applicable here since the groups are independent. Correlation is used to examine the relationship between two continuous variables, which is not what we are examining here.

Question 13

What type of multiple comparison procedure should be used if we want to divide the familywise error rate among the number of comparisons that we are performing?
A) Fisher's LSD
B) Bonferroni procedure
C) factorial ANOVA
D) paired samples t-test

Accepted Answer

The Bonferroni procedure is designed to control the familywise error rate by dividing alpha (the probability of making a Type I error) by the number of comparisons being made. This approach ensures that the overall probability of making a Type I error across all comparisons is still at or below alpha.

Question 14

The mean square error (MS_error) is a measure of A) how different the group means are. B) whether the dependent variable was measured incorrectly. C) how much variability there is within each group. D) whether the ANOVA is significant.

Accepted Answer

The mean square error (MS_error) is calculated by dividing the sum of squares within groups (S_error) by the degrees of freedom within groups. This value represents the amount of variability within each group, or the average amount of error in predicting an individual score from the group mean. Thus, C is the best choice as it accurately describes the measure of MS_error.

Question 15

When analyzing results of an ANOVA we are most interested in the _______.
A) F Statistic
B) t Statistic
C) R Squared
D) both a and c

Accepted Answer

The F statistic is the most important when analyzing results of an ANOVA because it tells us whether the means of two or more groups are significantly different from each other. The t statistic is used to determine whether there is a significant difference between two groups specifically. R squared is a measure of the proportion of variation in the dependent variable that is accounted for by the independent variable(s) in the model, but it is not the primary focus of an ANOVA analysis.

Question 16

In multiple comparison procedures, post-hoc tests are completed after the ANOVA. Why are post-hoc tests preferred over running several t-tests?
A) They decrease the probability of a Type I error.
B) They do not control familywise error rate.
C) It increases the probability of a Type I error.
D) They are more likely to be significant.

Accepted Answer

Post-hoc tests adjust for multiple comparisons, decreasing the probability of Type I errors. Running several t-tests without appropriate adjustments increases the overall probability of a Type I error.

Question 17

We want to compare the scores of different groups on a measure of reaction time. Three different groups were studied: patients with recent head injuries, patients with head injuries that occurred a year ago, and a control group of non-injured people. We want to know which group of people has the fastest reaction time. What is the best statistical test to use to find this out?
A) one way ANOVA
B) factorial ANOVA
C) paired samples t-test
D) correlation

Accepted Answer

The best statistical test to use in this scenario is a one way ANOVA since we are comparing the means of more than two independent groups. A factorial ANOVA is used to assess multiple independent variables, which is not needed in this case. A paired samples t-test is used when we want to compare two related groups, which is not the case here since we have three independent groups. Correlation is used to test the relationship between two continuous variables, which is not applicable in this scenario since we are comparing different groups.

Question 18

When we run a one-way ANOVA with four groups and obtain a significant F , the best effect-size measure to convey what that result tells us is A) . B) η². C) w ². D) all of the above

Accepted Answer

The answer of When we run a one-way ANOVA with...

Question 19

The book discusses an experiment by Merrell that examined the effects of Anthrax, Mozart, and no music on the amount of time it took a mouse to run a maze. To determine if there is an overall difference between the three groups, Merrell ran an ANOVA. To determine which means differed for each other, he ran a
A) regression.
B) repeated-measures t-test.
C) Bonferroni test.
D) chi-square.

Accepted Answer

The Bonferroni test is used to determine which means differ from each other in a multiple comparison situation, such as in this experiment where there are three groups being compared. It is a post-hoc test that adjusts the level of significance for each comparison to control the overall error rate. Therefore, the Bonferroni test is the appropriate choice in this scenario.

Question 20

A student wanted to determine if the mean number of times a student missed class was different for sophomores, juniors, and seniors. After collecting attendance data, the student ran an ANOVA and found that MS_groups was much larger than MS_error. This student can conclude that A) sophomores miss class more than juniors and seniors. B) there is a difference in the mean number of times sophomores, juniors, and seniors miss class. C) seniors miss class more than sophomores and juniors. D) there is no difference between the groups.

Accepted Answer

A large MS_groups compared to the MS_error indicates that there is a significant difference in the mean number of times students from each group miss class. Therefore, the student can conclude that there is a difference in the mean number of times sophomores, juniors, and seniors miss class.

Quiz 16: One-Way Analysis of Variance

The post-hoc test which holds the familywise error rate at .05 by running each individual test at the c/alpha level (# comparisons/alpha) is the

What are our choices for effect size measures for a one-way ANOVA?

When looking at multiple comparisons, the more tests that you run, the more likely that you will have a _______.

You want to control the _______ when multiple comparisons are being made?

Which of the following is not a multiple comparison procedure we have discussed in class or seen in the texts.

The null hypothesis behind a simple multiple-group analysis of variance is of the form:

Eysenck's study on recall as a function of level of processing showed

A common criticism of Fisher's LSD test is that

In the analysis of variance, MSGroups measures how different group means are, and MSerror measures variability within each group. If the null hypothesis were false, what would we expect to find?

The familywise error rate is

A researcher found significant differences in the mean running speeds of sprinters wearing shoes made by Nike, Reebok, and Adidas using an analysis of variance. The η2 calculated on the basis of group membership (based on which shoes were worn) equaled .16. The value of η2 shows that

What type of multiple comparison procedure should be used if we want to divide the familywise error rate among the number of comparisons that we are performing?

The mean square error (MSerror) is a measure of

When analyzing results of an ANOVA we are most interested in the _______.

In multiple comparison procedures, post-hoc tests are completed after the ANOVA. Why are post-hoc tests preferred over running several t-tests?

When we run a one-way ANOVA with four groups and obtain a significant F , the best effect-size measure to convey what that result tells us is

A student wanted to determine if the mean number of times a student missed class was different for sophomores, juniors, and seniors. After collecting attendance data, the student ran an ANOVA and found that MSgroups was much larger than MSerror. This student can conclude that

In the analysis of variance, MS_Groups measures how different group means are, and MS_error measures variability within each group. If the null hypothesis were false, what would we expect to find?

A researcher found significant differences in the mean running speeds of sprinters wearing shoes made by Nike, Reebok, and Adidas using an analysis of variance. The η² calculated on the basis of group membership (based on which shoes were worn) equaled .16. The value of η² shows that

The mean square error (MS_error) is a measure of

A student wanted to determine if the mean number of times a student missed class was different for sophomores, juniors, and seniors. After collecting attendance data, the student ran an ANOVA and found that MS_groups was much larger than MS_error. This student can conclude that