IBM SPSS by Example

A Practical Guide to Statistical Data Analysis
Second Edition
IBM SPSS by Example
January 2015 | 368 pages | Sage US
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Description

The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s “cut to the chase” IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.



Contents

Chapter 1: Introduction

  • Getting the Most Out of IBM SPSS by Example
  • A Brief Overview of the Statistical Process
  • Understanding Hypothesis Testing, Power, and Sample Size
  • Understanding the p-Value
  • Planning a Successful Analysis
  • Guidelines for Creating Data Sets
  • Preparing Excel Data for Import
  • Guidelines for Reporting Results
  • Opening Data Files for Examples

Chapter 2: Describing and Examining Data

  • Example Data Files
  • Describing Quantitative Data
  • Describing Categorical Data

Chapter 3: Creating and Using Graphs

  • Introduction to SPSS Graphs
  • Chart Builder
  • Graphboard Template Chooser
  • Legacy Plots
  • Scatterplots
  • Histograms
  • Bar Charts
  • Pie Charts
  • Box Plots

Chapter 4: Comparing One or Two Means Using the t-Test

  • One-Sample t-Test
  • Two-Sample t-Test
  • Paired t-Test

Chapter 5: Correlation and Regression

  • Correlation Analysis
  • Simple Linear Regression
  • Multiple Linear Regression

Chapter 6: Analysis of Categorical Data

  • Contingency Table Analysis
  • McNemar’s Test
  • Mantel-Haenszel Comparison
  • Tests of Interrater Reliability
  • Goodness-of-Fit Test
  • Other Measures of Association for Categorical Data

Chapter 7: Analysis of Variance and Covariance

  • One-Way ANOVA
  • Two-Way Analysis of Variance
  • Repeated-Measures Analysis of Variance
  • Analysis of Covariance

Chapter 8: Non-parametric Analysis Procedures

  • Spearman’s Rho
  • Mann-Whitney-Wilcoxon (Two Independent Groups Test)
  • Kruskal-Wallis Test
  • Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs
  • Friedman’s Test

Chapter 9: Logistic Regression

  • Simple Logistic Regression
  • Multiple Logistic Regression

Chapter 10: Factor Analysis

  • Factor Analysis Examples

Additional materials

Description

The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s “cut to the chase” IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.



Contents

Chapter 1: Introduction

  • Getting the Most Out of IBM SPSS by Example
  • A Brief Overview of the Statistical Process
  • Understanding Hypothesis Testing, Power, and Sample Size
  • Understanding the p-Value
  • Planning a Successful Analysis
  • Guidelines for Creating Data Sets
  • Preparing Excel Data for Import
  • Guidelines for Reporting Results
  • Opening Data Files for Examples

Chapter 2: Describing and Examining Data

  • Example Data Files
  • Describing Quantitative Data
  • Describing Categorical Data

Chapter 3: Creating and Using Graphs

  • Introduction to SPSS Graphs
  • Chart Builder
  • Graphboard Template Chooser
  • Legacy Plots
  • Scatterplots
  • Histograms
  • Bar Charts
  • Pie Charts
  • Box Plots

Chapter 4: Comparing One or Two Means Using the t-Test

  • One-Sample t-Test
  • Two-Sample t-Test
  • Paired t-Test

Chapter 5: Correlation and Regression

  • Correlation Analysis
  • Simple Linear Regression
  • Multiple Linear Regression

Chapter 6: Analysis of Categorical Data

  • Contingency Table Analysis
  • McNemar’s Test
  • Mantel-Haenszel Comparison
  • Tests of Interrater Reliability
  • Goodness-of-Fit Test
  • Other Measures of Association for Categorical Data

Chapter 7: Analysis of Variance and Covariance

  • One-Way ANOVA
  • Two-Way Analysis of Variance
  • Repeated-Measures Analysis of Variance
  • Analysis of Covariance

Chapter 8: Non-parametric Analysis Procedures

  • Spearman’s Rho
  • Mann-Whitney-Wilcoxon (Two Independent Groups Test)
  • Kruskal-Wallis Test
  • Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs
  • Friedman’s Test

Chapter 9: Logistic Regression

  • Simple Logistic Regression
  • Multiple Logistic Regression

Chapter 10: Factor Analysis

  • Factor Analysis Examples

Additional materials

SAGE Publishing Logo

IBM SPSS by Example

A Practical Guide to Statistical Data Analysis


January 2015 | 368 pages | Sage US

Format Published Date ISBN Price

The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s “cut to the chase” IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.




Table Of Contents:

  • Chapter 1: Introduction
  • Getting the Most Out of IBM SPSS by Example
  • A Brief Overview of the Statistical Process
  • Understanding Hypothesis Testing, Power, and Sample Size
  • Understanding the p-Value
  • Planning a Successful Analysis
  • Guidelines for Creating Data Sets
  • Preparing Excel Data for Import
  • Guidelines for Reporting Results
  • Opening Data Files for Examples
  • Chapter 2: Describing and Examining Data
  • Example Data Files
  • Describing Quantitative Data
  • Describing Categorical Data
  • Chapter 3: Creating and Using Graphs
  • Introduction to SPSS Graphs
  • Chart Builder
  • Graphboard Template Chooser
  • Legacy Plots
  • Scatterplots
  • Histograms
  • Bar Charts
  • Pie Charts
  • Box Plots
  • Chapter 4: Comparing One or Two Means Using the t-Test
  • One-Sample t-Test
  • Two-Sample t-Test
  • Paired t-Test
  • Chapter 5: Correlation and Regression
  • Correlation Analysis
  • Simple Linear Regression
  • Multiple Linear Regression
  • Chapter 6: Analysis of Categorical Data
  • Contingency Table Analysis
  • McNemar’s Test
  • Mantel-Haenszel Comparison
  • Tests of Interrater Reliability
  • Goodness-of-Fit Test
  • Other Measures of Association for Categorical Data
  • Chapter 7: Analysis of Variance and Covariance
  • One-Way ANOVA
  • Two-Way Analysis of Variance
  • Repeated-Measures Analysis of Variance
  • Analysis of Covariance
  • Chapter 8: Non-parametric Analysis Procedures
  • Spearman’s Rho
  • Mann-Whitney-Wilcoxon (Two Independent Groups Test)
  • Kruskal-Wallis Test
  • Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs
  • Friedman’s Test
  • Chapter 9: Logistic Regression
  • Simple Logistic Regression
  • Multiple Logistic Regression
  • Chapter 10: Factor Analysis
  • Factor Analysis Examples

Recent Product Reviews:

“This text not only helps the user to quickly navigate SPSS, but also provides critical aspects of each of the tests… I do not think that there is a better text for SPSS users who are looking for a quick introduction and succinct guidance.”
Philip J. Murphy, Monterey Institute of International Studies
“All in all, [this text] will become an indispensable tool for anyone that seeks to use statistical procedures to analyze data and to report the same effectively.”
Tyrone Bynoe, University of the Cumberlands
“[This text is] very readable and comprehensible for intermediate level students.”
Alan Davis, University of Colorado Denver

Recommendations