Question 1

The larger the number of data points, the easier it is to detect intervention effects.

Accepted Answer

A) True 
 B)False  True

Question 2

The chi-square approach can be used with auto-correlated data.

Accepted Answer

A) True 
 B)False  False

Question 3

When the results of performing several measures of statistical significance (such as those listed above) differ, one simply takes the most powerful among these tests and assumes that this answer is the most nearly correct one of the group.

Accepted Answer

A) True 
 B)False  False

Question 4

The randomization test is used to compensate when it is impossible to assign treatments randomly.

Accepted Answer

A) True 
 B)False

Question 5

The proportion/frequency approach can be used with dichotomous data.

Accepted Answer

A) True 
 B)False

Question 6

The X-Moving Range-chart (the three-standard-deviation-band approach) is useful with small numbers of data.

Accepted Answer

A) True 
 B)False

Question 7

The chi square has a long tradition of use with single-system designs, and is, therefore, one of the safest statistics to use.

Accepted Answer

A) True 
 B)False

Question 8

The C-Chart and the X-mR-Chart are both types of:

Accepted Answer

A)  Chi-square 
B)  SPC's 
C)  Proportion/Frequency Approaches 
D)  CDC's 
A)  Chi-square 
B)  SPC's 
C)  Proportion/Frequency Approaches 
D)  CDC's

Question 9

The t-test is a very powerful measure of statistical significance which can be calculated by hand or with a simple calculator, as well as by a computer program.

Accepted Answer

A) True 
 B)False

Question 10

The CDC approach has been shown to be useful even with data that are positively auto- correlated up to an autocorrelation of .50.

Accepted Answer

A) True 
 B)False

The larger the number of data points, the easier it is to detect intervention effects.

The chi-square approach can be used with auto-correlated data.

When the results of performing several measures of statistical significance (such as those listed above) differ, one simply takes the most powerful among these tests and assumes that this answer is the most nearly correct one of the group.

The randomization test is used to compensate when it is impossible to assign treatments randomly.

The proportion/frequency approach can be used with dichotomous data.

The X-Moving Range-chart (the three-standard-deviation-band approach) is useful with small numbers of data.

The chi square has a long tradition of use with single-system designs, and is, therefore, one of the safest statistics to use.

The C-Chart and the X-mR-Chart are both types of:

The t-test is a very powerful measure of statistical significance which can be calculated by hand or with a simple calculator, as well as by a computer program.

The CDC approach has been shown to be useful even with data that are positively auto- correlated up to an autocorrelation of .50.

Integrating Evaluation and Practice: Introduction to

Basic Principles of Conceptualization and Measurement

Specifying Problems and Goals: Targets of Intervention

Developing a Measurement and Recording Plan

Behavioral Observation

Individualized Rating Scales

Standardized Scales

Logs

Reactivity and Non-Reactive Measures

Selecting a Measure

Basic Principles of Single-System Designs

Baselining: Collecting Information Before Intervention

From the Case Study to the Basic Single-System Design: A-B

The Experimental Single-System Designs: A-B-A, A-B-A-B, B-A-B

Multiple Designs for Single Systems: Baselines, Targets, Crossovers, and Series

Changing Intensity Designs and Successive Intervention Designs

Designs for Comparing Interventions

Selecting a Design

Basic Principles of Analysis

Visual Analysis of Single-System Design Data

Descriptive Statistics

Selecting a Procedure for Analyzing Data

Not for Practitioners Alone: Evaluation for Clients, Administrators, Educators, and Students

Filters

Exam 22: Tests of Statistical Significance for Single-System Designs

The larger the number of data points, the easier it is to detect intervention effects.

The chi-square approach can be used with auto-correlated data.

When the results of performing several measures of statistical significance (such as those listed above) differ, one simply takes the most powerful among these tests and assumes that this answer is the most nearly correct one of the group.

The randomization test is used to compensate when it is impossible to assign treatments randomly.

The proportion/frequency approach can be used with dichotomous data.

The X-Moving Range-chart (the three-standard-deviation-band approach) is useful with small numbers of data.

The chi square has a long tradition of use with single-system designs, and is, therefore, one of the safest statistics to use.

The C-Chart and the X-mR-Chart are both types of:

The t-test is a very powerful measure of statistical significance which can be calculated by hand or with a simple calculator, as well as by a computer program.

The CDC approach has been shown to be useful even with data that are positively auto- correlated up to an autocorrelation of .50.

Integrating Evaluation and Practice: Introduction to

Basic Principles of Conceptualization and Measurement

Specifying Problems and Goals: Targets of Intervention

Developing a Measurement and Recording Plan

Behavioral Observation

Individualized Rating Scales

Standardized Scales

Logs

Reactivity and Non-Reactive Measures

Selecting a Measure

Basic Principles of Single-System Designs

Baselining: Collecting Information Before Intervention

From the Case Study to the Basic Single-System Design: A-B

The Experimental Single-System Designs: A-B-A, A-B-A-B, B-A-B

Multiple Designs for Single Systems: Baselines, Targets, Crossovers, and Series

Changing Intensity Designs and Successive Intervention Designs

Designs for Comparing Interventions

Selecting a Design

Basic Principles of Analysis

Visual Analysis of Single-System Design Data

Descriptive Statistics

Selecting a Procedure for Analyzing Data

Not for Practitioners Alone: Evaluation for Clients, Administrators, Educators, and Students

Filters