Quantitative Data Analysis for SPSS 12 and 13 A Guide for Social Scientists 1st Edition by Alan Bryman 9780415340816 0415340810

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ISBN 10: 0415340810
ISBN 13: 9780415340816 
Author: Alan Bryman

This new edition has been completely updated to accommodate the needs of users of SPSS Release 12 and 13 for Windows, whilst still being applicable to those using SPSS Release 11 and 10. Alan Bryman and Duncan Cramer provide a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS. No previous familiarity with computing or statistics is required to benefit from this step-by-step guide to techniques including: Non-parametric tests Correlation Simple and multiple regression Multivarate analysis of variance and covariance Factor analysis The authors discuss key issues facing the newcomer to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Each chapter contains worked examples to illustrate the points raised and ends with a comprehensive range of exercises which allow the reader to test their understanding of the topic. This new edition of this hugely successful textbook will guide the reader through the basics of quantitative data analysis and become an essential reference tool for both students and researchers in the social sciences.

Quantitative Data Analysis for SPSS 12 and 13 A Guide for Social Scientists 1st Table of contents:

Chapter 1: Data Analysis and the Research Process
Quantitative Data Analysis and the Research Process
Causality and Research Design
Survey Design and Causality
Exercises

Chapter 2: Analysing Data With Computers: First Steps With SPSS 12 and 13
Gaining Access to SPSS
The Data File
Entering and Editing Data In Data Editor
Naming Variables In Data Editor
Defining Other Aspects of Variables In Data Editor
Saving Data In Data Editor
Retrieving a Saved Data Editor File
Statistical Procedures
Saving and Printing Output
Help System
Leaving SPSS
Exercises
Appendix 2.1: The Job Survey Questions

Chapter 3: Analysing Data With Computers: Further Steps With SPSS 12 and 13
Selecting Cases
Relational Operators
Combining Logical Relations
Recoding the Values of Variables
Computing a New Variable
Missing Data and Computing Scores to Form New Measures
Exercises

Chapter 4: Concepts and Their Measurement
Types of Variable
Dimensions of Concepts
Validity and Reliability of Measures
Exercises

Chapter 5: Summarising Data
Frequency Distributions
Using SPSS to Produce Frequency Tables and Histograms
Measuring Central Tendency
Measuring Dispersion
Stems and Leaves, Boxes and Whiskers
The Shape of a Distribution
Exercises

Chapter 6: Sampling and Statistical Significance
Sampling
Sampling Problems
Statistical Significance
Exercises

Chapter 7: Bivariate Analysis: Exploring Differences Between Scores On Two Variables
Criteria for Selecting Bivariate Tests of Differences
Parametric Versus Non-Parametric Tests
Categorical Variables and Non-Parametric Tests
Non-Categorical Variables and Non-Parametric Tests
Non-Categorical Variables and Parametric Tests
Analysis of Variance for Three or More Related Means
Exercises

Chapter 8: Bivariate Analysis: Exploring Relationships Between Two Variables
Crosstabulation
Crosstabulation and Statistical Significance: The Chi-Square (χ2) Test
Correlation
Other Approaches to Bivariate Relationships
Regression
Overview of Types of Variable and Methods of Examining Relationships
Exercises

Chapter 9: Multivariate Analysis: Exploring Differences Among Three or More Variables
Multivariate Designs
Multivariate Analysis
Exercises

Chapter 10: Multivariate Analysis: Exploring Relationships Among Three or More Variables
Multivariate Analysis Through Contingency Tables
Multivariate Analysis and Correlation
Regression and Multivariate Analysis
Path Analysis
Exercises

Chapter 11: Aggregating Variables: Exploratory Factor Analysis
Correlation Matrix
Principal Components or Factors?
Number of Factors to Be Retained
Rotation of Factors
SPSS Factor Analysis Procedure

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Alan Bryman,Quantitative,Data Analysis