Question 1

The dfError in a one-factor between-subjects analysis of variance is equal to.

Accepted Answer

A) N - 1 
B) N + 1 
C) a - 1 
D) N - a 
A) N - 1 
B) N + 1 
C) a - 1 
D) N - a D

Question 2

If Fobs for a one-factor between-subjects design with two levels of the independent variable equals 4.00, then the value of tobs that would be obtained on the same set of scores is.

Accepted Answer

A) 16.00 
B) 8.00 
C) 2.00 
D) not enough 
A) 16.00 
B) 8.00 
C) 2.00 
D) not enough C

Question 3

The value of q for the Tukey HSD test depends upon the level of alpha, the number of means involved in the comparisons, and.

Accepted Answer

A) df for MSError 
B) df for MSTotal 
C) number of levels of the independent variable 
D) number of subjects in the experiment 
A) df for MSError 
B) df for MSTotal 
C) number of levels of the independent variable 
D) number of subjects in the experiment A

Question 4

In a one-factor multilevel design, the grand mean of all the scores is identified as.

Accepted Answer

A)  $\bar { X } _ { A }$ 
B)  Grand $\bar { X }$ 
C)  $\bar { X } _ { G }$ 
D)  $\bar { X }$ 
A)  $\bar { X } _ { A }$ 
B)  Grand $\bar { X }$ 
C)  $\bar { X } _ { G }$ 
D)  $\bar { X }$

Question 5

An experiment with one independent variable and three or more levels of the independent variable is called a(n) design.

Accepted Answer

A) one-factor t design 
B) one-factor multilevel design 
C) one-factor many levels design 
D) two-factor multilevel design 
A) one-factor t design 
B) one-factor multilevel design 
C) one-factor many levels design 
D) two-factor multilevel design

Question 6

If the results of an experiment using the one-factor between-subjects analysis of variance were summarized as F(2, 30) = 2.46, p > .05, then you would know that the total number of subjects used (N) was and the null hypothesis was .

Accepted Answer

A) 30; rejected 
B) 32; not rejected 
C) 33; not rejected 
D) 34; not rejected 
A) 30; rejected 
B) 32; not rejected 
C) 33; not rejected 
D) 34; not rejected

Question 7

If the results of an experiment using a one-factor between-subjects analysis of variance were summarized as F(2, 12) = 2.24, p > .05, then you know that the experiment used subjects and the Fobs was.

Accepted Answer

A) 12; statistically significant 
B) 15; statistically significant 
C) 12; nonsignificant 
D) 15; nonsignificant 
A) 12; statistically significant 
B) 15; statistically significant 
C) 12; nonsignificant 
D) 15; nonsignificant

Question 8

Which of the following equations is correct for partitioning a score in a one-factor between-subjects analysis of variance?

Accepted Answer

A)  $\bar { X } - \bar { X } _ { A } = \left( X - \bar { X } _ { Q } \right) + \left( \bar { X } _ { A } - \bar { X } _ { Q } \right)$ 
B)  $X _ { A } - \bar{X} _ { 0 } = \left( X -\bar{ X} _ { 0 } \right) + \left(\bar{ X} _ { 0 } - \bar{X }_ { A } \right)$ 
C)  $X - \bar { X } _ { G } = \left( \bar { X } _ { A } - \bar { X } _ { G } \right) + \left( X - \bar { X } _ { A } \right)$ 
D)  $X - \bar { X } _ { Q } = \left( \bar { X } _ { A } - \bar { X } _ { \theta } \right) - \left( X - \bar { X } _ { A } \right)$ 
A)  $\bar { X } - \bar { X } _ { A } = \left( X - \bar { X } _ { Q } \right) + \left( \bar { X } _ { A } - \bar { X } _ { Q } \right)$ 
B)  $X _ { A } - \bar{X} _ { 0 } = \left( X -\bar{ X} _ { 0 } \right) + \left(\bar{ X} _ { 0 } - \bar{X }_ { A } \right)$ 
C)  $X - \bar { X } _ { G } = \left( \bar { X } _ { A } - \bar { X } _ { G } \right) + \left( X - \bar { X } _ { A } \right)$ 
D)  $X - \bar { X } _ { Q } = \left( \bar { X } _ { A } - \bar { X } _ { \theta } \right) - \left( X - \bar { X } _ { A } \right)$

Question 9

The term represents within-groups error variation in the partitioned score of a subject in a one-factor between-subjects analysis of variance.

Accepted Answer

A)  $X - \bar { X } _ { A }$ 
B)  $\bar { X } _ { a } - \bar { X } _ { G }$ 
C)  $X = \bar { X } _ { G }$ 
D)  $X + \bar { Y } _ { A }$ 
A)  $X - \bar { X } _ { A }$ 
B)  $\bar { X } _ { a } - \bar { X } _ { G }$ 
C)  $X = \bar { X } _ { G }$ 
D)  $X + \bar { Y } _ { A }$

Question 10

The sampling distribution of the F statistic is.

Accepted Answer

A) positively skewed 
B) negatively skewed 
C) normal 
D) symmetrical around a mean of zero 
A) positively skewed 
B) negatively skewed 
C) normal 
D) symmetrical around a mean of zero

Question 11

The dfA in a one-factor between-subjects analysis of variance is equal to.

Accepted Answer

A) N - 1 
B) a - 2 
C) a - 1 
D) N - a 
A) N - 1 
B) a - 2 
C) a - 1 
D) N - a

Question 12

Both and are independent estimates of the population variance of scores in a one-factor between-subjects analysis of variance.

Accepted Answer

A) MSTotal; MSA 
B) MSTotal; MSError 
C) SSA; SSError 
D) MSA; MSError 
A) MSTotal; MSA 
B) MSTotal; MSError 
C) SSA; SSError 
D) MSA; MSError

Question 13

A one-factor multilevel design has.

Accepted Answer

A) one independent variable and one level of that independent variable 
B) two independent variables and one level of each independent variable 
C) two independent variables and two levels of each independent variable 
D) one independent variable and three or more levels of that independent variable 
A) one independent variable and one level of that independent variable 
B) two independent variables and one level of each independent variable 
C) two independent variables and two levels of each independent variable 
D) one independent variable and three or more levels of that independent variable

Question 14

If SSTotal = 100.00, SSA = 40.00, SSError = 60.00, dfTotal = 34, dfA = 4, and dfError = 30 in a one-factor between-subjects analysis of variance, then MSError =.

Accepted Answer

A) 1.18 
B) 0.10 
C) 2.00 
D) 10.00 
A) 1.18 
B) 0.10 
C) 2.00 
D) 10.00

Question 15

If the independent variable does have an effect, then MSA should be MSError, and the resulting F statistic should be in a one-factor between-subjects analysis of variance.

Accepted Answer

A) smaller than; less than 1.00 
B) nearly equal to; about 1.00 
C) larger than; greater than 1.00 
D) smaller than; greater than 1.00 
A) smaller than; less than 1.00 
B) nearly equal to; about 1.00 
C) larger than; greater than 1.00 
D) smaller than; greater than 1.00

Question 16

The error rate in an experiment is the probability of making at least one in the statistical tests conducted on the data.

Accepted Answer

A) correct decision 
B) Type II error 
C) significant finding 
D) Type I error 
A) correct decision 
B) Type II error 
C) significant finding 
D) Type I error

Question 17

Assume that an experiment used a one-factor between-subjects design with four groups and that each group consisted of eight participants. What would be the value of a?

Accepted Answer

A) 8 
B) 4 
C) 32 
D) 10 
A) 8 
B) 4 
C) 32 
D) 10

Question 18

The systematic variation between groups in a one-factor between-subjects analysis of variance is reflected in.

Accepted Answer

A) MSA 
B) MSError 
C) dfA 
D) dfError 
A) MSA 
B) MSError 
C) dfA 
D) dfError

Question 19

If the null hypothesis is rejected in a one-factor between-subjects analysis of variance on three groups, then it may be concluded that the.

Accepted Answer

A) three sample means were not obtained from populations with identical means 
B) three sample means were obtained from populations with identical means 
C) sample means are not equal to the population means 
D) variances of the sample means are not equal to the variances of the means in the populations 
A) three sample means were not obtained from populations with identical means 
B) three sample means were obtained from populations with identical means 
C) sample means are not equal to the population means 
D) variances of the sample means are not equal to the variances of the means in the populations

Question 20

The term represents the effect of the independent variable and sampling error in the partitioned score of a subject in a one-factor between-subjects analysis of variance.

Accepted Answer

A)  $X - \bar { X } _ { A }$ 
B)  $X - \bar { X } _ { \mathrm { G } }$ 
C)  $X + \bar { X } _ { A }$ 
D)  $\bar { X } _ { A } - \bar { X } _ { G }$ 
A)  $X - \bar { X } _ { A }$ 
B)  $X - \bar { X } _ { \mathrm { G } }$ 
C)  $X + \bar { X } _ { A }$ 
D)  $\bar { X } _ { A } - \bar { X } _ { G }$

The dfError in a one-factor between-subjects analysis of variance is equal to.

If Fobs for a one-factor between-subjects design with two levels of the independent variable equals 4.00, then the value of tobs that would be obtained on the same set of scores is.

The value of q for the Tukey HSD test depends upon the level of alpha, the number of means involved in the comparisons, and.

In a one-factor multilevel design, the grand mean of all the scores is identified as.

An experiment with one independent variable and three or more levels of the independent variable is called a(n) design.

If the results of an experiment using the one-factor between-subjects analysis of variance were summarized as F(2, 30) = 2.46, p > .05, then you would know that the total number of subjects used (N) was and the null hypothesis was .

If the results of an experiment using a one-factor between-subjects analysis of variance were summarized as F(2, 12) = 2.24, p > .05, then you know that the experiment used subjects and the Fobs was.

Which of the following equations is correct for partitioning a score in a one-factor between-subjects analysis of variance?

The term represents within-groups error variation in the partitioned score of a subject in a one-factor between-subjects analysis of variance.

The sampling distribution of the F statistic is.

The dfA in a one-factor between-subjects analysis of variance is equal to.

Both and are independent estimates of the population variance of scores in a one-factor between-subjects analysis of variance.

A one-factor multilevel design has.

If SSTotal = 100.00, SSA = 40.00, SSError = 60.00, dfTotal = 34, dfA = 4, and dfError = 30 in a one-factor between-subjects analysis of variance, then MSError =.

If the independent variable does have an effect, then MSA should be MSError, and the resulting F statistic should be in a one-factor between-subjects analysis of variance.

The error rate in an experiment is the probability of making at least one in the statistical tests conducted on the data.

Assume that an experiment used a one-factor between-subjects design with four groups and that each group consisted of eight participants. What would be the value of a?

The systematic variation between groups in a one-factor between-subjects analysis of variance is reflected in.

If the null hypothesis is rejected in a one-factor between-subjects analysis of variance on three groups, then it may be concluded that the.

The term represents the effect of the independent variable and sampling error in the partitioned score of a subject in a one-factor between-subjects analysis of variance.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

Looking at Data: Measures of Variability

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

Two-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters

Exam 10: One-Factor Between-Subjects Analysis of Variance

The dfError in a one-factor between-subjects analysis of variance is equal to.

If Fobs for a one-factor between-subjects design with two levels of the independent variable equals 4.00, then the value of tobs that would be obtained on the same set of scores is.

The value of q for the Tukey HSD test depends upon the level of alpha, the number of means involved in the comparisons, and.

In a one-factor multilevel design, the grand mean of all the scores is identified as.

An experiment with one independent variable and three or more levels of the independent variable is called a(n) design.

If the results of an experiment using the one-factor between-subjects analysis of variance were summarized as F(2, 30) = 2.46, p > .05, then you would know that the total number of subjects used (N) was and the null hypothesis was .

If the results of an experiment using a one-factor between-subjects analysis of variance were summarized as F(2, 12) = 2.24, p > .05, then you know that the experiment used subjects and the Fobs was.

Which of the following equations is correct for partitioning a score in a one-factor between-subjects analysis of variance?

The term represents within-groups error variation in the partitioned score of a subject in a one-factor between-subjects analysis of variance.

The sampling distribution of the F statistic is.

The dfA in a one-factor between-subjects analysis of variance is equal to.

Both and are independent estimates of the population variance of scores in a one-factor between-subjects analysis of variance.

A one-factor multilevel design has.

If SSTotal = 100.00, SSA = 40.00, SSError = 60.00, dfTotal = 34, dfA = 4, and dfError = 30 in a one-factor between-subjects analysis of variance, then MSError =.

If the independent variable does have an effect, then MSA should be MSError, and the resulting F statistic should be in a one-factor between-subjects analysis of variance.

The error rate in an experiment is the probability of making at least one in the statistical tests conducted on the data.

Assume that an experiment used a one-factor between-subjects design with four groups and that each group consisted of eight participants. What would be the value of a?

The systematic variation between groups in a one-factor between-subjects analysis of variance is reflected in.

If the null hypothesis is rejected in a one-factor between-subjects analysis of variance on three groups, then it may be concluded that the.

The term represents the effect of the independent variable and sampling error in the partitioned score of a subject in a one-factor between-subjects analysis of variance.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

Looking at Data: Measures of Variability

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

Two-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters