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Communication Research Statistics

Communication Research Statistics

June 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.
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  
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  
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  
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
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.

Quality and Operation Management, University of Johannesburg
February 12, 2015

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ISBN: 9780761929871

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