Statistics for the Health Sciences is a highly readable and accessible textbook on understanding statistics for the health sciences, both conceptually and via the SPSS programme. The authors give clear explanations of the concepts underlying statistical analyses and descriptions of how these analyses are applied in health science research without complex maths formulae. The textbook takes students from the basics of research design, hypothesis testing and descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter. The strengths and weaknesses of different techniques are critically appraised throughout, and the authors emphasise how they may be used both in research and to inform best practice care in health settings. Exercises and tips throughout the book allow students to practice using SPSS. The companion website provides further practical experience of conducting statistical analyses. Features include: * multiple choice questions for both student and lecturer use * full Powerpoint slides for lecturers * practical exercises using SPSS * additional practical exercises using SAS and R This is an essential textbook for students studying beginner and intermediate level statistics across the health sciences.
By making introductory statistics interesting through comparing data on today's student generation with their parents' generation, and asking students to consider how people change as they grow older, the book uses data on subjective beliefs (such as freedom of speech and abortion) as well objective characteristics (years of schooling, marital status) to teach basic statistics using SPSS.
Understanding and Using Advanced Statistics is a comprehensive, practical guide for postgraduate students advising how and when to use more advanced statistical methods. Perfect for students without a mathematical background, the authors refresh important basics such as descriptive statistics and research design as well as introducing essential upper level techniques to cater for the advanced student.
This book provides an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). Beginning with an overview of the univariate general linear model, this volume defines the key steps in analyzing linear model data and introduces multivariate linear model analysis as a generalization of the univariate model. Richard F. Haase focuses on multivariate measures of association for four common multivariate test statistics, presents a flexible method for testing hypotheses on models, and emphasizes the multivariate procedures attributable to Wilks, Pillai, Hotelling, and Roy. The volume concludes with a discussion of canonical correlation analysis that is shown to subsume all the multivariate procedures discussed in previous chapters. The analyses are illustrated throughout the text with three running examples drawing from several disciples, including personnel psychology, anthropology, environmental epidemiology, and neuropsychology.
An Introduction to Basic and Advanced Multilevel Modeling
The classic text in multilevel analysis, dealing with everything you need to know, has been hugely revised and added to and is supported by all the software. A must-have for modellers.
How do you present or organize your statistical or numerical data so that it is accessible and meaningful for your readers or audience? Graphing Statistics & Data introduces the technique and art of producing good charts. Carefully written with many examples and illustrations, the book begins with an introduction to the building blocks of ......
The focus in this Second Edition is on logistic regression models for individual level (but aggregate or grouped) data. Multiple cases for each possible combination of values of the predictors are considered in detail and examples using SAS and SPSS are included. New to this edition: * more detailed consideration of grouped as opposed to casewise ......
This is the ideal textbook for any course in statistical methods across the health and social sciences and a perfect starter book for students, researchers and professionals alike.
