Question 1

Which of the following tests is most appropriate for analyzing scores obtained from a between-subjects design with ordinal measures of the dependent variable?

Accepted Answer

A) tind. 
B) Wilcoxon signed-ranks test. 
C) Chi-square test of independence. 
D) Mann-Whitney U test. 
A) tind. 
B) Wilcoxon signed-ranks test. 
C) Chi-square test of independence. 
D) Mann-Whitney U test.

Question 2

To meet the assumptions for use of the chi-square test of independence, the minimum expected frequency for any cell in a contingency table larger than 2 x 2 should not be less than.

Accepted Answer

A) 2 
B) 5 
C) 10 
D) a value determined by multiplying the marginals 
A) 2 
B) 5 
C) 10 
D) a value determined by multiplying the marginals

Question 3

If a 3 × 3 contingency table is presented, then you know that a study used variables each with categories.

Accepted Answer

A) three; two 
B) two; three 
C) three; three 
D) nine; three 
A) three; two 
B) two; three 
C) three; three 
D) nine; three

Question 4

A table arranged in rows and columns and used in a chi-square test of independence is called a table.

Accepted Answer

A) histogram 
B) contingency 
C) frequency 
D) marginal 
A) histogram 
B) contingency 
C) frequency 
D) marginal

Question 5

A rows-by-columns contingency table is analyzed with a.

Accepted Answer

A) chi-square test of independence 
B) chi-square goodness-of-fit test 
C) Mann-Whitney U test 
D) Wilcoxon signed-ranks test 
A) chi-square test of independence 
B) chi-square goodness-of-fit test 
C) Mann-Whitney U test 
D) Wilcoxon signed-ranks test

Which of the following tests is most appropriate for analyzing scores obtained from a between-subjects design with ordinal measures of the dependent variable?

To meet the assumptions for use of the chi-square test of independence, the minimum expected frequency for any cell in a contingency table larger than 2 x 2 should not be less than.

If a 3 × 3 contingency table is presented, then you know that a study used variables each with categories.

A table arranged in rows and columns and used in a chi-square test of independence is called a table.

A rows-by-columns contingency table is analyzed with a.

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

One-Factor Between-Subjects Analysis of Variance

Two-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

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Exam 15: Nonparametric Tests

Which of the following tests is most appropriate for analyzing scores obtained from a between-subjects design with ordinal measures of the dependent variable?

To meet the assumptions for use of the chi-square test of independence, the minimum expected frequency for any cell in a contingency table larger than 2 x 2 should not be less than.

If a 3 × 3 contingency table is presented, then you know that a study used variables each with categories.

A table arranged in rows and columns and used in a chi-square test of independence is called a table.

A rows-by-columns contingency table is analyzed with a.

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

One-Factor Between-Subjects Analysis of Variance

Two-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Filters