Question 1

A goodness-of-fit test tests can use χ2 to determine whether a program or policy exceeds a standard or norm.

Accepted Answer

A) True 
 B)False  True

Question 2

Practical significance examines the strength of relationships.

Accepted Answer

A) True 
 B)False  True

Question 3

(Optional, Appendix): When adding a control variable causes a previously significant relationship to become insignificant, the result is called explanation.

Accepted Answer

A) True 
 B)False  True

Question 4

(Optional, Appendix): other nonparametric examples include Kendals τ-b, Goodman-Kruskal's τ and the McNemar test.

Accepted Answer

A) True 
 B)False

Question 5

We first determine practical significance and then determine statistical significance.

Accepted Answer

A) True 
 B)False

Question 6

The critical value is compared against the test statistic for the purpose of hypothesis testing.

Accepted Answer

A) True 
 B)False

Question 7

The last step in hypothesis testing is looking up the critical value of test statistics.

Accepted Answer

A) True 
 B)False

Question 8

A 5% level of significance suggests a higher level of confidence than a 1% level of significance.

Accepted Answer

A) True 
 B)False

Question 9

The null hypothesis is stated in Greek letters because the null hypothesis refers to relations in the population.

Accepted Answer

A) True 
 B)False

Question 10

Kendall's τ-c can vary from +1.00 to -1.00. Scores of less than |0.25| indicate weak relationships; scores between |0.25| and |0.50| indicate moderate relationships; and scores of greater than |0.50| indicate strong relationships.

Accepted Answer

A) True 
 B)False

Question 11

The concept of statistical significance relates to the matter of confidence.

Accepted Answer

A) True 
 B)False

Question 12

When two variables are unrelated to each other, the χ2 test statistic is large.

Accepted Answer

A) True 
 B)False

Question 13

Practical significance examines by how much one variable changes as a result of changing another.

Accepted Answer

A) True 
 B)False

Question 14

Degree of freedom is a concept associated with determining the critical value.

Accepted Answer

A) True 
 B)False

Question 15

It is easier to reject the null hypothesis with a large sample than with a small sample.

Accepted Answer

A) True 
 B)False

Question 16

Generally, a critical value will be larger at the 1% level of significance than at the 5% level of significance.

Accepted Answer

A) True 
 B)False

Question 17

Kendall's τ-c is a nonparametric statistic which should never be used because it is less useful than χ2.

Accepted Answer

A) True 
 B)False

Question 18

A relationship that is reported as being significant at "p = 0.945" is statistically significant.

Accepted Answer

A) True 
 B)False

Question 19

When using the χ2 test statistic, "expected" frequencies are those that researchers observe in the sample.

Accepted Answer

A) True 
 B)False

Question 20

The χ2 test statistic is useful for determining the direction of relationships.

Accepted Answer

A) True 
 B)False

A goodness-of-fit test tests can use χ² to determine whether a program or policy exceeds a standard or norm.

Practical significance examines the strength of relationships.

(Optional, Appendix): When adding a control variable causes a previously significant relationship to become insignificant, the result is called explanation.

(Optional, Appendix): other nonparametric examples include Kendals τ-b, Goodman-Kruskal's τ and the McNemar test.

We first determine practical significance and then determine statistical significance.

The critical value is compared against the test statistic for the purpose of hypothesis testing.

The last step in hypothesis testing is looking up the critical value of test statistics.

A 5% level of significance suggests a higher level of confidence than a 1% level of significance.

The null hypothesis is stated in Greek letters because the null hypothesis refers to relations in the population.

Kendall's τ-c can vary from +1.00 to -1.00. Scores of less than |0.25| indicate weak relationships; scores between |0.25| and |0.50| indicate moderate relationships; and scores of greater than |0.50| indicate strong relationships.

The concept of statistical significance relates to the matter of confidence.

When two variables are unrelated to each other, the χ² test statistic is large.

Practical significance examines by how much one variable changes as a result of changing another.

Degree of freedom is a concept associated with determining the critical value.

It is easier to reject the null hypothesis with a large sample than with a small sample.

Generally, a critical value will be larger at the 1% level of significance than at the 5% level of significance.

Kendall's τ-c is a nonparametric statistic which should never be used because it is less useful than χ².

A relationship that is reported as being significant at "p = 0.945" is statistically significant.

When using the χ² test statistic, "expected" frequencies are those that researchers observe in the sample.

The χ² test statistic is useful for determining the direction of relationships.

Why Statistics for Public Managers and Policy Analysts

Research Design

Conceptualization and Measurement

Measuring and Managing Performance: Present and Future

Data Collection

Central Tendency

Measures of Dispersion

Contingency Tables

Getting Results

Introducing Inference: Estimation From Samples

The T-Test

Analysis of Variance Anova

Simple Regression

Multiple Regression

Logistic and Time Series Regression

Survey of Other Techniques

Filters

Exam 11: Hypothesis Testing With Chi-Square

A goodness-of-fit test tests can use χ2 to determine whether a program or policy exceeds a standard or norm.

Practical significance examines the strength of relationships.

(Optional, Appendix): When adding a control variable causes a previously significant relationship to become insignificant, the result is called explanation.

(Optional, Appendix): other nonparametric examples include Kendals τ-b, Goodman-Kruskal's τ and the McNemar test.

We first determine practical significance and then determine statistical significance.

The critical value is compared against the test statistic for the purpose of hypothesis testing.

The last step in hypothesis testing is looking up the critical value of test statistics.

A 5% level of significance suggests a higher level of confidence than a 1% level of significance.

The null hypothesis is stated in Greek letters because the null hypothesis refers to relations in the population.

Kendall's τ-c can vary from +1.00 to -1.00. Scores of less than |0.25| indicate weak relationships; scores between |0.25| and |0.50| indicate moderate relationships; and scores of greater than |0.50| indicate strong relationships.

The concept of statistical significance relates to the matter of confidence.

When two variables are unrelated to each other, the χ2 test statistic is large.

Practical significance examines by how much one variable changes as a result of changing another.

Degree of freedom is a concept associated with determining the critical value.

It is easier to reject the null hypothesis with a large sample than with a small sample.

Generally, a critical value will be larger at the 1% level of significance than at the 5% level of significance.

Kendall's τ-c is a nonparametric statistic which should never be used because it is less useful than χ2.

A relationship that is reported as being significant at "p = 0.945" is statistically significant.

When using the χ2 test statistic, "expected" frequencies are those that researchers observe in the sample.

The χ2 test statistic is useful for determining the direction of relationships.

Why Statistics for Public Managers and Policy Analysts

Research Design

Conceptualization and Measurement

Measuring and Managing Performance: Present and Future

Data Collection

Central Tendency

Measures of Dispersion

Contingency Tables

Getting Results

Introducing Inference: Estimation From Samples

The T-Test

Analysis of Variance Anova

Simple Regression

Multiple Regression

Logistic and Time Series Regression

Survey of Other Techniques

Filters

A goodness-of-fit test tests can use χ² to determine whether a program or policy exceeds a standard or norm.

When two variables are unrelated to each other, the χ² test statistic is large.

Kendall's τ-c is a nonparametric statistic which should never be used because it is less useful than χ².

When using the χ² test statistic, "expected" frequencies are those that researchers observe in the sample.

The χ² test statistic is useful for determining the direction of relationships.