Table Of Content

Introduction to Statistics with SPSS for Social Science Visit the Introduction to Statistics with SPSS for Social Science Companion Website at www.routledge.com/books/details/9781408237595/ • Datasets from the book allowing you to analyse and practise. Introduction to Statistics with SPSS for Social Science Gareth Norris Aberystwyth University Faiza Qureshi City University London Dennis Howitt University of Loughborough Duncan Cramer University of Loughborough First published 2012 by Pearson Education Limited Published 2013 by Routledge 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN 711 Third Avenue, New York, NY 10017, USA Routledge is an imprint of the Taylor & Francis Group, an informa business Copyright © 2012, Taylor & Francis. The rights of Gareth Norris, Faiza Qureshi, Dennis Howitt and Duncan Cramer to be identified as authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. ISBN 13: 978-1-4082-3759-5 (pbk) British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Norris, Gareth. Introduction to statistics with SPSS for social science / Gareth Norris, Faiza Qureshi. — 1st ed. p. cm. Includes bibliographical references and index. ISBN 978-1-4082-3759-5 1. SPSS (Computer file) 2. Social sciences—Statistical methods—Computer programs. I. Qureshi, Faiza, 1981- II. Title. HA32.N64 2012 005.5’5—dc23 2011052975 Typeset in 9.5/12pt Sabon by 35 Brief contents Guided tour Introduction List of figures List of tables List of boxes List of calculation boxes Acknowledgements Part 1 Descriptive statistics 1 Why you need statistics: types of data 2 Describing variables: tables and diagrams 3 Describing variables numerically: averages, variation and spread 4 Shapes of distributions of scores 5 Standard deviation, z-scores and standard error: the standard unit of measurement in statistics 6 Relationships between two or more variables: diagrams and tables 7 Correlation coefficients: the Pearson correlation and Spearman’s rho 8 Regression and standard error Part 2 Inferential statistics 9 The analysis of a questionnaire/survey project 10 The related t-test: comparing two samples of correlated/related scores 11 The unrelated t-test: comparing two samples of unrelated/uncorrelated score 12 Chi-square: differences between samples of frequency data Part 3 Introduction to analysis of variance 13 Analysis of variance (ANOVA): introduction to one-way unrelated or uncorrelated ANOVA 14 Two-way analysis of variance for unrelated/uncorrelated scores: two studies for the price of one? 15 Analysis of covariance (ANCOVA): controlling for additional variables 16 Multivariate analysis of variance (MANOVA) Part 4 More advanced statistics and techniques 17 Partial correlation: spurious correlation, third or confounding variables (control variables), suppressor variables 18 Factor analysis: simplifying complex data 19 Multiple regression and multiple correlation 20 Multinomial logistic regression: distinguishing between several different categories or groups 21 Binomial logistic regression 22 Log-linear methods: the analysis of complex contingency tables Appendices Glossary References Index Contents Guided tour Introduction List of figures List of tables List of boxes List of calculation boxes Acknowledgements Part 1 Descriptive statistics 1 Why you need statistics: types of data Overview 1.1 Introduction 1.2 Variables and measurement 1.3 Statistical significance 1.4 SPSS guide: an introduction Key points 2 Describing variables: tables and diagrams Overview 2.1 Introduction 2.2 Choosing tables and diagrams 2.3 Errors to avoid 2.4 SPSS analysis 2.5 Pie diagram of category data 2.6 Bar chart of category data 2.7 Histograms Key points 3 Describing variables numerically: averages, variation and spread Overview 3.1 Introduction: mean, median and mode 3.2 Comparison of mean, median and mode 3.3 The spread of scores: variability 3.4 Probability 3.5 Confidence intervals 3.6 SPSS analysis Key points 4 Shapes of distributions of scores Overview 4.1 Introduction 4.2 Histograms and frequency curves 4.3 The normal curve 4.4 Distorted curves 4.5 Other frequency curves 4.6 SPSS analysis Key points 5 Standard deviation, z-scores and standard error: the standard unit of measurement in statistics Overview 5.1 Introduction 5.2 What is standard deviation? 5.3 When to use standard deviation 5.4 When not to use standard deviation 5.5 Data requirements for standard deviation 5.6 Problems in the use of standard deviation 5.7 SPSS analysis 5.8 Standard error: the standard deviation of the means of samples 5.9 When to use standard error 5.10 When not to use standard error 5.11 SPSS analysis for standard error Key points 6 Relationships between two or more variables: diagrams and tables Overview 6.1 Introduction 6.2 The principles of diagrammatic and tabular presentation 6.3 Type A: both variables numerical scores 6.4 Type B: both variables nominal categories 6.5 Type C: one variable nominal categories, the other numerical scores 6.6 SPSS analysis Key points 7 Correlation coefficients: the Pearson correlation and Spearman’s rho Overview 7.1 Introduction 7.2 Principles of the correlation coefficient 7.3 Some rules to check out 7.4 Coefficient of determination 7.5 Data requirements for correlation coefficients 7.6 SPSS analysis 7.7 Spearman’s rho – another correlation coefficient 7.8 SPSS analysis for Spearman’s rho 7.9 Scatter diagram using SPSS 7.10 Problems in the use of correlation coefficients Key points 8 Regression and standard error Overview 8.1 Introduction 8.2 Theoretical background and regression equations 8.3 When and when not to use simple regression 8.4 Data requirements for simple regression 8.5 Problems in the use of simple regression 8.6 SPSS analysis 8.7 Regression scatterplot 8.8 Standard error: how accurate are the predicted score and the regression equations? Key points Part 2 Inferential statistics 9 The analysis of a questionnaire/survey project Overview 9.1 Introduction 9.2 The research project 9.3 The research hypothesis 9.4 Initial variable classification 9.5 Further coding of data 9.6 Data cleaning 9.7 Data analysis 9.8 SPSS analysis Key points 10 The related t-test: comparing two samples of correlated/related scores Overview 10.1 Introduction 10.2 Dependent and independent variables 10.3 Theoretical considerations 10.4 SPSS analysis 10.5 A cautionary note Key points 11 The unrelated f-test: comparing two samples of unrelated/uncorrelated scores Overview 11.1 Introduction 11.2 Theoretical considerations 11.3 Standard deviation and standard error 11.4 A cautionary note 11.5 Data requirements for the unrelated t-test 11.6 When not to use the unrelated t-test 11.7 Problems in the use of the unrelated t-test 11.8 SPSS analysis Key points