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Communication Research Statistics
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Communication Research Statistics



April 2006 | 600 pages | SAGE Publications, Inc
Written in an accessible style using simple and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research in communication and the social sciences. This book is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel.
 
Preface
 
Section One: Introduction to Statistical Analyses
 
1. Using Statistics to Conduct Quantitative Research
A World of Statistics

 
Why Do Quantitative Research?

 
Typical Steps Involved in Quantitative Research

 
 
2. Collecting Data on Variables
Variables and Hypotheses

 
Measurement of Variables

 
Sampling

 
 
Section Two: Descriptive Statistics
 
3. Central Tendency
Doing a Study and Reporting Descriptive Information

 
Typical Measures of Central Tendency

 
Relations among Mean Median and Mode

 
 
4. Looking at Variability and Dispersion
Assessing Dispersion

 
The Relationship Between Measures of Central Tendency and Variability

 
Examining Distributions

 
 
5. Correlations
The Notion of Correlation

 
Elements of the Correlation

 
Computing the Pearson Product-Moment Correlation

 
Matters Affecting Correlations

 
Methods of Correlations

 
Alternative Forms of Association

 
 
6. Ensuring Reliability and Validity
The Notion of Measurement Acceptability

 
How to Do a study of Measurement Adequacy

 
Reliability

 
Validity

 
The Relation of Validity to Reliability

 
 
Section Three: Inferential Statistics
 
7. Statistical Significance Hypothesis Testing when Comparing Two Means
Doing a Study that Tests a Hypothesis of Differences Between Means

 
Assumptions in Parametric Hypothesis Testing

 
Comparing Sample and Population Means

 
Comparing the Means of Two Sample Groups: The Two-Sample t Test

 
Comparing Means Differences of Paired Scores: The Paired Difference t

 
Assessing Power

 
 
8. Comparing More than Two Means: One-Way Analysis of Variance
Hypothesis Testing for More than Two Means

 
The Analysis of Variance Hypothesis Test

 
What after ANOVA? Multiple Comparison Tests

 
Extensions of Analysis of Variance

 
 
9. Factorial Analysis of Variance
Doing a Study that Involves More than One Independent Variable

 
Types of Effect to Test

 
Computing the Fixed-Effect ANOVA

 
Random and Mixed-Effects Designs

 
 
Section Four: Nonparametric Tests
 
10. Nonparametric Tests for Categorical Variables
The Notion of "Distribution-Free" Statistics

 
Conducting a Study that Requires Nonparametric Tests of Categorical Data

 
The Chi-Square Test

 
Alternatives to Chi-Square for Frequency Data

 
 
11. Nonparametric Tests for Rank Order Dependent Variables
Doing a Study Involving Ordinal Dependent Variables

 
Comparing Ranks of One Group to Presumed Populations Characteristics: Analogous Tests to One-Sample t Tests

 
Comparing Ranks from Two Sample Groups

 
Comparing Ranks from More than Two Sample Groups: Analogous Tests to One-Way ANOVA

 
 
Section Five: Advanced Statistical Applications
 
12. Meta-Analysis
Meta-Analysis: An Alternative to Artistic Literature Reviews

 
Conducting the Meta-Analysis Study

 
Using Computer Techniques to Perform Meta-Analysis

 
 
13. Multiple Regression Correlation
Contrasting Bivariate Correlation and Multiple Regression Correlation

 
Components of Multiple Correlations

 
How to Do a Multiple Regression Correlation Study

 
 
14. Extensions of Multiple Regression Correlation
Using Categorical Predictors

 
Contrasting Full and Reduced Models: Hierarchical Analysis

 
Interaction Effects

 
Examining Nonlinear Effects

 
 
15. Exploratory Factor Analysis
Forms of Factor Analysis

 
The Notion of Multivariate Analyses

 
Exploratory Factor Analysis

 
 
16. Confirmatory Factor Analysis Through the AMOS Program
The Notion of Confirmatory Factor Analysis

 
Using the AMOS Program for Confirmatory Factor Analysis

 
 
17. Modeling Communication Behavior
The Goals of Modeling

 
How to Do a Modeling Study

 
Path Models

 
Using the AMOS Program

 
 
Appendix A: Using Excel XP to Analyze Data
Getting Ready to Run Statistics With Excel

 
Handling Data

 
Using the Menu Bar

 
Toolbars

 
How to Run Statistics From the Analysis ToolPak

 
Using Functions

 
 
Appendix B: Using SPSS 12 for Windows
How to enter and Screen Your Own Data in SPSS

 
How to Enter Data From a Word Processor

 
How to Create Indexes From Scales

 
Commands in the SPSS System

 
Dealing With Output

 
Alternative Editing Environments

 
 
Appendix C: Tables
 
References
 
Index
 
About the Author

"Reinard sets forth a solid intermediate level statistics book that could serve students in advanced researcg classes quite well. In essence, this text would help with the quagmire many students encounter when reading statistics books."

S.-A. Welch
The Review of Communication

"Each chapter provides a minimum of formulae and avoids complex numerical computations. To some, this approach will appear to be the end of the world as we know it. But, in my experience, detailed examination of statistical formulae via hand computations leads to anxiety about arithmetic rather than a deepening of understanding of statistics for a majority of students. It is only after the anxiety is dealt with, and the student has a degree of facility with statistics, that a deepening understanding can occur with such methods. The book adopts a conceptual rather than a computational approach, and this is to be commended."

Stephen Cox
Australian Centre for Business Research, Queensland University of Technology

A well-written book, suitable for both undergraduate and postgraduate students. The book cover both elementary and intermediate statistics, and provides some background information about the formula used to calculate the statistics without alienating the reader.

Dr Mansour Pourmehdi
Department of Sociology, Manchester Metropolitan University
March 6, 2015

A very good book easy to understand and apply the context covered in ones own research. Has been welcomed by students in my course.

Dr JOHN FRANCIS AGWA-EJON
Quality and Operation Management, University of Johannesburg
February 12, 2015

Sample Materials & Chapters

Chapter 7

Chapter 9

Chapter 17


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John C. Reinard

John C. Reinard (Ph.D., Southern California) is a professor of Human Communication Studies at California State University, Fullerton. He regularly teaches graduate and undergraduate courses in research methods, quantitative research, persuasion, critical thinking, and argumentation. He received his Ph.D. from the University of Southern California in 1975, after which he served on the faculties at California Polytechnic State University, San Luis Obispo and Arizona State University. He also has served as a master instructor in statistical process control for Motorola. ... More About Author

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