SPSS survival manual : a step by step guide to data analysis using IBM SPSS

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書誌事項

SPSS survival manual : a step by step guide to data analysis using IBM SPSS

Julie Pallant

Open University Press, 2021

7th ed

  • : pbk

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注記

First published 2001

Includes bibliographical references (p. 353-357) and index

内容説明・目次

内容説明

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.

目次

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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