Statistics Without Maths for Psychology

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Examples from the literature highlight a key piece of research in the area. Chapter summaries enable you to revise the main points of the chapter after you’ve read it. Numerous examples in each chapter illustrate the key points. The companion website, available at www.pearsoned.co.uk/dancey, is updated with interactive features including: • An interactive hyperlinked flow chart guiding you through each step of choosing an analysis • An expanded bank of Multiple Choice Questions allowing you to test your knowledge of each chapter • Extra data sets and exercises for each chapter to allow you to put what you’ve learnt into practice It is also possible to have more than three levels (e.g. 6 ¨ 4 or 7 ¨ 3), but interpretation then becomes a problem. We do not just want to say ‘there is a significant relationship between variable A and variable B’. We would also like to be able to say something about the direction of the relationship. For instance, in our smoke/drink example, we could see, from looking at the cells, that the significant relationship referred to the positive association between drinking and smoking. When we have larger contingency tables, it can be difficult to disentangle all the various relationships. Table 9.8 3 ¨ 3 contingency table

Inferential tests, which show us whether the relationship between the variables is likely to have been due to sampling error, assuming the null hypothesis is true. Sampling error SPSS: obtaining measures of central tendency Graphically describing data SPSS: generating graphical descriptives Scattergrams SPSS: generating scattergrams Sampling error and relationships between variables The normal distribution Variation or spread of distributions SPSS: obtaining measures of variation Other characteristics of distributions Non-normal distributions SPSS: displaying the normal curve on histograms Writing up your descriptive statistics For uncorrelated DVs, how do we examine the relative contributions of the individual DVs to the combined DVs when our IV has only two conditions? (a) Conduct separate t-tests and adjust V to keep down the familywise error rate (b) Look at the multivariate effect size of the combined DVs (c) Check that Box’s M is significant (d) Both (a) and (b) above 9. If we had three DVs and found a multivariate difference, what level of V would we set for each t-test to keep the overall V at 5%? (a) (b) (c) (d) Text Personal Reflection Box on page 199 from Emeritus Professor Lesley J. Rogers; Personal Reflection Box on page 228 from Dr Marie-Pascale Noël; Personal Reflection Box on page 246 from Professor Robert Rosenthal; Personal Reflection Box on pages 245 –6 from Professor Geoffrey Loftus; Activity 8.1 from Professor Robert Rosenthal; Personal Reflection Box on page 310 from Dr. Kirstie Soar; Personal Reflection Box on page 415 from Dr. Norah Vincent and Ms. Samantha Lewycky; Quote on page 470 from Validation of the Beck Depression Inventory for a Portuguese-speaking Chinese community in Brazil, Brazilian Journal of Medical and Biological Research, 38(3), 399–408 (Wang, Y-P., Andrade, L.H. and Gorenstein, C. 2005); Personal Reflection Box on page 474 from Dr. Anne-Marie Joyce; Personal Reflection Box on page 531 from Scott Barry Kaufman We are grateful to the following reviewers: Dr David T. Field, University of Reading Dr Hayley Ness, Open University Dr Michael Pilling, Oxford Brookes University Dr Asiya Siddique, Manchester Metropolitan University We are grateful to the academics who have provided personal reflections: Dr Ann-Marie Joyce Dr Scott Barry Kaufman Ms Samantha Lewycky Professor Geoffrey Loftus Dr Marie-Pascale Noël Professor Lesley Rogers Professor Robert Rosenthal Dr Kirstie Soar Dr Norah Vincent The authors would like to thank Dr Joy Coogan and Vera Dancey for reading the proofs.More definitions explain the key terms you need to understand statistics Up-to-date examples from the literature keep you informed of current research NEW interviews with researchers bring statistics to life NEW full-colour design makes it even easier to follow the steps in SPSS NEW SPSS exercises allow you to learn by using the software Full guidance on using version 18 of SPSS, as well as earlier versions of the software Companion website We would urge you to make as much use as possible of the resources available to you on the companion website. When you get on to the site you will see that it is broken down into resources for each chapter. For each chapter you will find SPSS Statistics dataset files which are simply the data for the examples that we provide in each chapter. You can access these to ensure that you have input data correctly or so that you can carry out the same analyses that we present in each chapter to make sure that you get the same results. Also, on the website you will find additional multiple choice questions. If you find that you have made mistakes in the multiple choice questions provided in the book you should go back through the chapter and try to make sure that you fully understand the concepts presented. It wouldn’t make sense for you to then test yourself using the same multiple choice questions and so we have provided the additional ones on the companion website. As another means of testing yourself and to help you actively learn we provide additional SPSS Statistics exercises for each chapter and a step-by-step guide to the analysis to conduct on this data and how to interpret the output. Finally, you will find links to interesting and useful websites which are relevant to the concepts being covered in each chapter. Chapter overview Introduction Sources of variance Designs suitable for factorial ANOVA ANOVA terminology Two between-participants independent variables SPSS: analysis of two between-participants factors Two within-participants variables SPSS: ANOVA with two within-participants factors One between- and one within-participants variable SPSS: ANOVA with one between-participants factor and one within-participants factor Effect size: `2 can be converted to a statistic called Cramer’s V – this is interpreted in the same way as any other correlation coefficient. Luckily, this is available through SPSS. Chapter overview Bivariate correlations SPSS: bivariate correlations – Pearson’s r SPSS: obtaining a scattergram matrix First- and second-order correlations SPSS: partial correlations – Pearson’s r Patterns of correlations

Only the DVs should be normally distributed All DVs and all IVs should be normally distributed All DVs and all possible linear combinations of the DVs should be normally distributed All of the above The purpose of linear regression SPSS: drawing the line of best fit SPSS: linear regression analysis Multiple regressionTables Tables on pages 78 and 117 from Effects of physical positions on sleep architectures and post-nap functions among habitual nappers, Biological Psychology, 83, 207–13 (Zhao, D., Zhang, Q., Fu, M., Tang, Y. and Zhao, Y. 2010). With permission from Elsevier; Table on page 201 from Counting on Working Memory When Learning to Count and to Add: A Preschool Study, Developmental Psychology, 45 (6), 1630–1643 (Noël, P. 2009), Copyright © 2009 by the American Psychological Association. Reproduced with permission. The official citation that should be used in referencing this material is doi:10.1037/a0016224. No further reproduction or distribution is permitted without written permission from the American Psychological Association; Table on page 202 from Perceived stigma, illness intrusiveness and quality of life in men and women with irritable bowel syndrome, Psychology, Health and Medicine, 7 (4), 381–95 (Dancey, C.P., Hutton-Young, S.A., Moye, S. and Devins, G.M. 2002), Reprinted by permission of the publisher (Taylor & Francis Ltd, http://www.informaworld.com); Table on page 227 from Inferencing processes after right hemisphere brain damage: maintenance of