Question 1

If a researcher summates the scales of a construct that has five items, this means that the researcher would:

Accepted Answer

A)  Sum the high and low questions within a construct 
B)  Sum each of the items within a construct 
C)  Sum the standard deviations within the five items 
D)  Sum the five items and divide by the standard deviation 
A)  Sum the high and low questions within a construct 
B)  Sum each of the items within a construct 
C)  Sum the standard deviations within the five items 
D)  Sum the five items and divide by the standard deviation

Question 2

Dummy coding refers to:

Accepted Answer

A)  Using the mean value for missing data 
B)  Using one and zero to refer to having a property or not having that property 
C)  If one does not know the actual value of a data point, the researcher adds what the researcher expects the value to be 
D)  Placing a zero in a data set for missing values 
A)  Using the mean value for missing data 
B)  Using one and zero to refer to having a property or not having that property 
C)  If one does not know the actual value of a data point, the researcher adds what the researcher expects the value to be 
D)  Placing a zero in a data set for missing values

Question 3

A codebook is a printed record of the names and labels for each variable and value label.

Accepted Answer

A) True 
 B)False

Question 4

Factor loadings less than .30 are considered low.

Accepted Answer

A) True 
 B)False

Question 5

When coding data it is best to use letters for nominal variables. For example, in statistical programs one should input an "M" for male and an "F" for female.

Accepted Answer

A) True 
 B)False

If a researcher summates the scales of a construct that has five items, this means that the researcher would:

Dummy coding refers to:

A codebook is a printed record of the names and labels for each variable and value label.

Factor loadings less than .30 are considered low.

When coding data it is best to use letters for nominal variables. For example, in statistical programs one should input an "M" for male and an "F" for female.

Definitions, Purposes, and Dimensions of Research

Planning a Quantitative Research Project

Variables, Research Questions, and Hypotheses

Research Approaches

Randomized Experimental and Quasi-Experimental Designs

Single-Subject Designs

Nonexperimental Approachesdesigns

Internal Validity

Sampling and Introduction to External Validity

Measurement and Descriptive Statistics

Measurement Reliability

Measurement Validity

Types of Data Collection Techniques

Ethical Issues in Conducting the Study

Making Inferences From Sample Data I: The Null Hypothesis Significance Testing Approach

Making Inferences From Sample Data II: the Evidence-Based Approach

General Design Classifications for Selection of Difference Statistical Methods

Selection of Appropriate Statistical Methods: Integration of Design and Analysis

Data Analysis and Interpretation: Basic Difference Questions

Analysis and Interpretation of Basic Associational Research Questions

Analysis and Interpretation of Complex Research Questions

Evaluating Research Validity: Part I

Evaluating Research Validity: Part II

Evaluating Research for Evidence-Based Practice

Writing the Research Report

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Exam 15: Practical Issues in Data Collection and Coding

If a researcher summates the scales of a construct that has five items, this means that the researcher would:

Dummy coding refers to:

A codebook is a printed record of the names and labels for each variable and value label.

Factor loadings less than .30 are considered low.

When coding data it is best to use letters for nominal variables. For example, in statistical programs one should input an "M" for male and an "F" for female.

Definitions, Purposes, and Dimensions of Research

Planning a Quantitative Research Project

Variables, Research Questions, and Hypotheses

Research Approaches

Randomized Experimental and Quasi-Experimental Designs

Single-Subject Designs

Nonexperimental Approachesdesigns

Internal Validity

Sampling and Introduction to External Validity

Measurement and Descriptive Statistics

Measurement Reliability

Measurement Validity

Types of Data Collection Techniques

Ethical Issues in Conducting the Study

Making Inferences From Sample Data I: The Null Hypothesis Significance Testing Approach

Making Inferences From Sample Data II: the Evidence-Based Approach

General Design Classifications for Selection of Difference Statistical Methods

Selection of Appropriate Statistical Methods: Integration of Design and Analysis

Data Analysis and Interpretation: Basic Difference Questions

Analysis and Interpretation of Basic Associational Research Questions

Analysis and Interpretation of Complex Research Questions

Evaluating Research Validity: Part I

Evaluating Research Validity: Part II

Evaluating Research for Evidence-Based Practice

Writing the Research Report

Filters