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Statistics Explained is an accessible introduction to statistical concepts and ideas. It makes few assumptions about the reader's statistical knowledge, carefully explaining each step of the analysis and the logic behind it. Statistics Explained: provides a clear explanation of statistical analysis and the key statistical tests employed in analysing research data gives accessible explanations of how and why statistical tests are used includes a wide range of practical, easy-to-understand worked examples.
Building on the international success of earlier editions, this fully updated revision includes developments in statistical analysis, with new sections explaining concepts such as bootstrapping and structural equation modelling. A new chapter – 'Samples and Statistical Inference' – explains how data can be analysed in detail to examine its suitability for certain statistical tests. The friendly and straightforward style of the text makes it accessible to all those new to statistics, as well as more experienced students requiring a concise guide. It is suitable for students and new researchers in disciplines including Psychology, Education, Sociology, Sports Science, Nursing, Communication, and Media and Business Studies.
Presented in full colour and with an updated, reader-friendly layout, this new edition also comes with a companion website featuring supplementary resources for students. Unobtrusive cross-referencing makes it the ideal companion to Perry R. Hinton's SPSS Explained, also published by Routledge. Perry R. Hinton has many years of experience in teaching statistics to students from a wide range of disciplines and his understanding of the problems students face forms the basis of Statistics Explained.
1 Introduction
2 Descriptive Statistics
3 Standard Scores
4 Introduction to Hypothesis Testing
5 Sampling
6 Hypothesis Testing with One Sample
7 Selecting Samples for Comparison
8 Hypothesis Testing with Two Samples
9 Significance, Error and Power
10 Samples and Statistical Inference
11 Introduction to the Analysis of Variance
12 One Factor Independent Measures ANOVA
13 Multiple Comparisons
14 One Factor Repeated Measures ANOVA
15 The Interaction of Factors in the Analysis of Variance
16 The Two Factor ANOVA
17 Two Sample Nonparametric Analyses
18 One Factor ANOVA for Ranked Data
19 Analysing Frequency Data: Chi-Square
20 Linear Correlation and Regression
21 Multiple Correlation and Regression
22 Complex Analyses
23 An Introduction to the General Linear Model
24 Postscript
Notes
Glossary
References
Appendix
Index
Perry R. Hinton is a psychologist, and has worked for over twenty five years in four British universities, from lecturer to Head of Department. He has taught in the areas of cognitive and social psychology, and research methods and statistics, primarily to psychology and communication and media students; but also to a wide range of students studying subjects including nursing, social work, linguistics, philosophy and education. He has written four textbooks and edited the Psychology Focus series for Routledge.
"I have been a fan of Hinton's Statistics Explained from its first edition and I still think this is one of the best introductory level texts on the market. The combination of clear explanation, simple worked examples and friendly style make an excellent choice for introductory classes in psychology and related disciplines."
– Thom Baguley, Nottingham Trent University, UK
"This book really delivers on its title: It provides in-depth explanations of the reasoning behind statistical analyses. It gives students a solid understanding of some of the most important current statistical analyses, with all their conditions and pitfalls. That is exactly what is needed. [...] I have used Statistics Explained in both graduate and undergraduate introduction courses to statistics, and will definitely continue using it. In the 3rd edition, I am happy to see improvements over the already excellent 2nd edition, for example in the explanation of confidence intervals. There is a great new chapter on samples and statistical inference, and a postscript that makes an excellent point about biases in the field as a whole."
– Katrin Erk, The University of Texas at Austin, USA
"I am using Statistics Explained to demystify statistics in applied fields and for this it is doing a perfect job. All essential statistical approaches are covered in an easy to understand way and the used examples provide confirmation of the learned theory."
– Reyer Zwiggelaar, Aberystwyth University, UK
