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. The book:
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 this book.
"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
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