# Statistics Without Maths for Psychology 7th Edition

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## Book Preface

It seems incredible to us that it is now 18 years since our book was first published. We have been amazed at how well the book has been received and thankful for the kind words tutors and students alike have said about it. In this seventh edition of the book we have kept true to our vision for the book to provide conceptual explanations of statistical concepts without making you suffer through the formulae. We have built upon the strengths of the previous editions and updated our examples from the literature, updated some of the practical exercises, provided reflections from authors of published research and responded, with revised explanations, to a number of reviewers who kindly provided feedback on the sixth edition.

We wrote this book primarily for our students, most of whom disliked mathematics, and could not understand why they had to learn mathematical formulae when their computer software performed the calculations for them. They were not convinced by the argument that working through calculations gave them an understanding of the test â€“ neither were we. We wanted them to have a conceptual understanding of statistics and to enjoy data analysis. Over the past 20 years we have had to adapt our teaching to large groups of students, many of whom have no formal training in mathematics. We found it was difficult to recommend some of the traditional statistics textbooks â€“ either they were full of mathematical formulae, and perceived by the students as dull or boring, or they were simple, statistical cookbook recipes, which showed them how to perform calculations, but gave them no real understanding of what the statistics meant. We therefore decided to write this book, which seeks to give students a conceptual understanding of statistics while avoiding the distraction of formulae and calculations.

Another problem we found with recommending statistics textbooks was the over-reliance on the probability value in the interpretation of results. We found it difficult to convince them to take effect size, and confidence intervals, into consideration when the textbooks that were available made no mention of the debates around hypothesis testing, but simply instructed students to say p 6 0.05 is significant and p 7 0.05 is not significant! We hope in writing this book that students will become more aware of such issues.

We also wanted to show students how to incorporate the results of their analysis into laboratory reports, and how to interpret results sections of journal articles. Until recently, statistics books ignored this aspect of data analysis. Of course, we realise that the way we have written our example â€˜results sectionsâ€™ will be different from the way that other psychologists would write them. Students can use these sections to gain confidence in writing their own results, and hopefully they will build on them, as they progress through their course. We have tried to simplify complex, sometimes very complex, concepts. In simplifying, there is a trade-off in accuracy. We were aware of this when writing the book, and have tried to be as accurate as possible, while giving the simplest explanation. We are also aware that some students do not use SPSS (an IBM company*) for their data analysis. IBMÂ® SPSSÂ® Statistics, however, is the most commonly used statistical package for the social sciences, and this is why the text is tied so closely to SPSS. Students not using this package should find the book useful anyway.

This edition of the book has been updated for use with SPSS version 23 and earlier. As with the sixth edition of the book we have included information about the authors of articles which we have drawn upon in the writing of this book â€“ and have included photos of them where possible â€“ strictly with their permission, of course. We also asked them why they had chosen their particular research topic, and whether they had encountered any problems in the running of the experiment/study. We thought this would enrich the text. Although we have updated many examples from the literature, we have left in some early studies because they illustrate exactly the points made in the text. Some reviewers thought there should be more challenging activities and/or multiple choice questions. Therefore, we have added activities which are based on examples from the literature, and require students to interpret the material, in their own words. They can then compare their interpretation with the authorsâ€™ interpretation.

We hope that students who read the book will not only learn from it, but also enjoy our explanations and examples. We also hope that as a result of reading this book students will feel confident in their ability to perform their own statistical analyses.

### Brief contents

Preface xvi
Guided tour xx
Acknowledgements xxii
1 Variables and research design 1
2 Introduction to SPSS 25
3 Descriptive statistics 42
4 Probability, sampling and distributions 97
5 Hypothesis testing and statistical significance 134
6 Correlational analysis: Pearsonâ€™s r 174
7 Analyses of differences between two conditions: the t-test 217
8 Issues of significance 246
9 Measures of association 265
10 Analysis of differences between three or more conditions 298
11 Analysis of variance with more than one IV 328
12 Regression analysis 377
13 Analysis of three or more groups partialling out effects of a covariate 414
14 Introduction to factor analysis 446
15 Introduction to multivariate analysis of variance (MANOVA) 481
16 Non-parametric statistics 516
Answers to activities and SPSS exercises 551
Appendix 1: Table of z-scores and the proportion of the standard normal
distribution falling above and below each score 592
Appendix 2: Table r to zr 595
Index 597