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Data Analysis with SPSS by Stephen A. Sweet, Ithaca College ZIP OR PDF for sale 

Table of Contents

All chapters begin with an “Overview” and conclude with “Summary,” “Key Terms,” “References and Further Reading,” and “Exercises.”

1.Key Concepts in Social Science Research.

Developing Research Questions.

Theory and Hypothesis.

Indicators.

Variables.

Causality.

Data Sets.

2.Getting Started: Accessing, Examining, and Saving Data.

The Layout of SPSS®.

Defining and Saving New Data Set.

Loading and Examining an Existing File.

Dropping and Adding Variables in the Data Editor.

Naming and Labeling Variables.

Merging and Importing Files.

3.Univariate Analysis.

Sorting Data.

Measures of Central Tendency.

Exploring Distributions of Data.

Computing New Variables.

Recoding Existing Variables.

4.Bivariate Analysis.

Statistical Significance.

Analyzing Bivariate Relationships.

Cross Tabulations.

Comparison of Means.

Correlations.

5.Graphing.

Univariate Graphing.

Bivariate Graphing.

6.Multivariate Analysis: Regression.

The Regression Equation: A Bivariate Example.

Data and Multiple Regression.

Multivariate Regression: An Example.

Graphing a Multivariate Regression.

7.Multivariate Analysis: Logistic Regression.

Logistic Regression.

Logistic Regression: A Bivariate Example.

Multivariate Logistic Regression: An Example.

8.Writing a Research Report.

The Title.

The Abstract.

The Introduction.

The Literature Review.

The Methods.

The Findings.

The Conclusion.

9.Research Projects.

Secondary Data Analysis.

Publicly Available Data.

Potential Research Projects.

Research Project 1: Racism.

Research Project 2: Suicide.

Research Project 3: Politics.

Research Project 4: Criminality.

Research Project 5: Welfare.

Research Project 6: Sexual Behavior.

Research Project 7: Education.

Research Project 8: Your Topic.

Appendix 1.

STATES.SAV Descriptives.

Appendix 2.

GSS96.SAV File Information.

Appendix 3.

Variable Label Abbreviations.

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