SPSS survival manual : a step by step guide to data analysis using IBM SPSS
Author(s)
Bibliographic Information
SPSS survival manual : a step by step guide to data analysis using IBM SPSS
Open University Press, 2021
7th ed
- : pbk
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Note
First published 2001
Includes bibliographical references (p. 353-357) and index
Description and Table of Contents
Description
The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software.
In her bestselling guide, Julie Pallant takes you through the entire research process, helping you choose the right data analysis technique for your project. This edition has been updated to include up to SPSS version 26. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report.
For both beginners and experienced users in Psychology, Sociology, Health Sciences, Medicine, Education, Business and related disciplines, the SPSS Survival Manual is an essential text. It is illustrated throughout with screen grabs, examples of output and tips, and is also further supported by a website with sample data and guidelines on report writing.
This seventh edition is fully revised and updated to accommodate changes to IBM SPSS procedures.
Table of Contents
Preface
Data files and website
Introduction and overview
Part One Getting started
1 Designing a study
2 Preparing a codebook
3 Getting to know IBM SPSS Statistics
Part Two Preparing the data file
4 Creating a data file and entering data
5 Screening and cleaning the data
Part Three Preliminary analyses
6 Descriptive statistics
7 Using graphs to describe and explore the data
8 Manipulating the data
9 Checking the reliability of a scale
10 Choosing the right statistic
Part Four Statistical techniques to explore relationships among variables
11 Correlation
12 Partial correlation
13 Multiple regression
14 Logistic regression
15 Factor analysis
Part Five Statistical techniques to compare groups
16 Non-parametric statistics
17 T-tests
18 One-way analysis of variance
19 Two-way between-groups ANOVA
20 Mixed between-within subjects analysis of variance
21 Multivariate analysis of variance
22 Analysis of covariance
Appendix: Details of data files
Recommended reading
References
Index
by "Nielsen BookData"
