Synopses & Reviews
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:
- 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 this book.
Hinton presents a textbook for a course introducing statistics toundergraduate or graduate students of the social and life sciences, health, business, and communication. The topics include descriptivestatistics, standard scores, hypothesis testing with one sample, selecting samples for comparison, samples and statistical inference,multiple comparisons, the interaction of factors in the analysis of variance, the two-factor ANOVA, two-sample nonparametric analysis,multiple correlation and regression, complex analysis, and an introduction to the general linear model.Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com)