Overview

Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today.   Written in ten manageable chapters, this book first introduces students to the approach researchers use to frame research questions and the logic of establishing causal relations. Students are then oriented to the SPSS program and how to examine data sets. Subsequent chapters guide them through univariate analysis, bivariate analysis, graphic analysis, and multivariate analysis. Students conclude their course by learning how to write a research report and by engaging in their own research project.   Each book is packaged with a disk containing the GSS (General Social Survey) file and the States data files. The GSS file contains 100 variables generated from interviews with 2,900 people, concerning their behaviors and attitudes on a wide variety of issues such as abortion, religion, prejudice, sexuality, and politics. The States data allows comparison of all 50 states with 400 variables indicating issues such as unemployment, environment, criminality, population, and education. Students will ultimately use these data to conduct their own independent research project with SPSS.   Note: MySearchLab does not come automatically packaged with this text. To purchase MySearchLab, please visit: www.mysearchlab.com or you can purchase a ValuePack of the text + MySearchLab with Pearson eText (at no additional cost). ValuePack ISBN-10: 0205863728 / ValuePack ISBN-13: 9780205863723

Full Product Details

Author:   Stephen Sweet ,  Karen Grace-Martin ,  Karen Grace-Martin
Publisher:   Pearson Education (US)
Imprint:   Pearson
Edition:   4th edition
Dimensions:   Width: 21.50cm , Height: 1.50cm , Length: 27.60cm
Weight:   0.680kg
ISBN:  

9780205019670

ISBN 10:   0205019676
Pages:   288
Publication Date:   05 May 2011
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

TABLE OF CONTENTS: 1. BRIEF 2. COMPREHENSIVE   BRIEF TABLE OF CONTENTS   Chapter 1  •   Key Concepts in Social Science Research         Chapter 2  •   Getting Started: Accessing, Examining, and Saving   Chapter 3   •  Univariate Analysis: Descriptive Statistics          Chapter 4   • Constructing Variables      Chapter 5   •  Assessing Association through Bivariate Analysis           Chapter 6   •  Comparing Group Means through Bivariate Analysis             Chapter 7   •  Modeling Relationships of Multiple Variables with Linear Regression                                  Chapter 8   •  Logistic Regression         Chapter 9   •  Writing a Research Report          Chapter 10 •  Research Projects                                                   COMPREHENSIVE TABLE OF CONTENTS    Chapter 1  • Key Concepts in Social Science Research                   Overview                      Framing Topics Into Research Questions                        Theories and Hypotheses                         Population and Samples                                     Relationships and Causality                     Data Sets                                                   Parts of a Data Set                                     Reliability and Validity                              Summary                      Key Terms                    Exercises               Chapter 2 •  Getting Started: Accessing, Examining, and Saving Data                                   Overview                             The Layout of SPSS                  Types of Variables                    Initial Settings                                        Defining and Saving a New Data Set                              Managing Data Sets: Dropping and Adding Variables, Merging Data Sets             Dropping and Adding Variables                                      Merging and Importing Files                                               Loading and Examining an Existing File                  Summary                      Key Terms                         Exercises               Chapter 3  •  Univariate Analysis: Descriptive Statistics                     Overview                        Why Do Researchers Perform Univariate Analysis?                                Exploring Distributions of Scale Variables                                                   Exploring Distributions of Categorical Variables                            Summary                      Key Terms                   Exercises             Chapter 4  • Constructing Variables                  Overview                      Why Construct New Variables From Existing Data?                   Recoding Existing Variables                               Computing New Variables                                 Recording Computations Using Syntax                Minimizing Missing Values in Computing New Variables                    Summary                      Key Terms                    Exercises            Chapter 5  •  Assessing Association through Bivariate Analysis                       Overview                      Why Do We Need Significance Tests?                         Analyzing Bivariate Relationships Between Two Categorical Variables                Analyzing Bivariate Relationships Between Two Scale Variables                         Summary                         Key Terms                   Exercises            Chapter 6  •  Comparing Group Means through Bivariate Analysis                         Overview                         One-Way Analysis of Variance                 Post-hoc Tests                                         Assumptions of ANOVA                          Graphing the Results of ANOVA                       T tests                           Summary                      Key Terms                   Exercises            Chapter 7  •  Modeling Relationships of Multiple Variables with Linear Regression                                       Overview                       The Advantages of Modeling Relationships in Multiple Regression                        Linear Regression: A Bivariate Example                                                   Multiple Linear Regression                     Other Concerns In Applying Linear Regression                 Building Multiple Variable Models                      Summary                           Key Terms                    Exercises                Chapter 8  •  Logistic Regression                     Overview                         What Is Logistic Regression?                             When Can I Use a Logistic Regression?                          Understanding  Relationships through Probabilities                       Logistic Regression: A Bivariate Example                                      Multiple Variable Logistic Regression: An Example                        Summary                          Key Terms                       Exercises              Chapter 9  •  Writing a Research Report                      Overview                      Writing Style and Audience                                   The Structure of a Report                                     Summary                          Key Terms                        Exercises                      Chapter 10  •  Research Projects                                   Potential Research Projects                                   Research Project 1: Racism                                   Research Project 2: Suicide                                    Research Project 3: Criminality                              Research Project 4: Welfare and Other Public Aid Consumption                               Research Project 5: Sexual Behavior                       Research Project 6: Education                              Research Project 7: Health                                Research Project 8: Happiness                           Research Project 9: Your Topic                              

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