SPSS Survival Manual - Julie Pallant

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Résumé :
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.


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Biographie:
Julie Pallant has spent many years helping students overcome statistics phobia. She is currently a research coordinator in the Faculty of Medicine, Dentistry and Health Sciences at the University of Melbourne, Australia. Previously she has also worked as an applied statistics lecturer, counselling psychologist, and has taught psychology, statistics and research methods at a number of universities....

Sommaire:
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

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