Question 1

Because of the independence restriction, the McNemar test cannot be used on dependent samples.

Accepted Answer

A) True 
 B)False

Question 2

When using the nominal scale to assess political-party affiliation,

Accepted Answer

A)  the strength of each individual's party loyalty must be established 
B)  the subjects within each category must be rank-ordered with respect to affiliative strength 
C)  each and every subject must receive a different scale number 
D)  the individuals must be independently grouped as to party preference 
A)  the strength of each individual's party loyalty must be established 
B)  the subjects within each category must be rank-ordered with respect to affiliative strength 
C)  each and every subject must receive a different scale number 
D)  the individuals must be independently grouped as to party preference

Question 3

Chi square is a far more powerful test than is either t or F.

Accepted Answer

A) True 
 B)False

Question 4

Every 2 by 2 chi square, regardless of sample size, contains only 1 degree of freedom.

Accepted Answer

A) True 
 B)False

Question 5

The degrees of freedom for a 2 by 2 chi square must always equal

Accepted Answer

A)  4 
B)  2 
C)  1 
D)  none of these 
A)  4 
B)  2 
C)  1 
D)  none of these

Question 6

Chi square may never be used with nominal data.

Accepted Answer

A) True 
 B)False

Question 7

The null hypothesis for chi square states that the observed frequencies are equal to the expected frequencies.

Accepted Answer

A) True 
 B)False

Question 8

The chi square statistical test may handle data from

Accepted Answer

A)  experimental research 
B)  post-facto research 
C)  both of these 
D)  neither of these 
A)  experimental research 
B)  post-facto research 
C)  both of these 
D)  neither of these

Question 9

Chi square, like t and F, always tests the hypothesis of

Accepted Answer

A)  association 
B)  correlation 
C)  difference 
D)  a priori events 
A)  association 
B)  correlation 
C)  difference 
D)  a priori events

Because of the independence restriction, the McNemar test cannot be used on dependent samples.

When using the nominal scale to assess political-party affiliation,

Chi square is a far more powerful test than is either t or F.

Every 2 by 2 chi square, regardless of sample size, contains only 1 degree of freedom.

The degrees of freedom for a 2 by 2 chi square must always equal

Chi square may never be used with nominal data.

The null hypothesis for chi square states that the observed frequencies are equal to the expected frequencies.

The chi square statistical test may handle data from

Chi square, like t and F, always tests the hypothesis of

Introduction to Statistics

Percentages, Graphs and Measures of Central Tendency

Measures of Variability

The Normal Curve and Z Score

Z Scores, T Scores and Other Normal Curve Transformations

Probability

Statistics and Parameters

Parameter Estimates

The Fundamentals of Research Methodology

The Hypothesis of Difference

The Hypothesis of Association: Correlation

Analysis of Variance

Regression Analysis

Repeated-Measures and Matched-Subjects Designs Interval Data

Non-Parametrics Revisited: the Ordinal Case

Tests and Measurements

Filters

Exam 13: Nominal Categorical Data and the Chi Square

Because of the independence restriction, the McNemar test cannot be used on dependent samples.

When using the nominal scale to assess political-party affiliation,

Chi square is a far more powerful test than is either t or F.

Every 2 by 2 chi square, regardless of sample size, contains only 1 degree of freedom.

The degrees of freedom for a 2 by 2 chi square must always equal

Chi square may never be used with nominal data.

The null hypothesis for chi square states that the observed frequencies are equal to the expected frequencies.

The chi square statistical test may handle data from

Chi square, like t and F, always tests the hypothesis of

Introduction to Statistics

Percentages, Graphs and Measures of Central Tendency

Measures of Variability

The Normal Curve and Z Score

Z Scores, T Scores and Other Normal Curve Transformations

Probability

Statistics and Parameters

Parameter Estimates

The Fundamentals of Research Methodology

The Hypothesis of Difference

The Hypothesis of Association: Correlation

Analysis of Variance

Regression Analysis

Repeated-Measures and Matched-Subjects Designs Interval Data

Non-Parametrics Revisited: the Ordinal Case

Tests and Measurements

Filters