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Specifically written for students in the health sciences, this book covers simple statistical concepts and then shows how to analyse data using SPSS.
John MacInnes takes the fear out of statistics for students, and helps to raise the standards of their quantitative methods skills, by clearly and accessibly introducing all that’s needed to know about using secondary data and working with IBM SPSS Statistics.
Specifically written for students in the health sciences, this book covers simple statistical concepts and then shows how to analyse data using SPSS.
From bestselling author Andy Field comes the version for SAS users with all the features (and wit) of the original.
Doing Statistics With SPSS is derived from the authors' many years of experience teaching undergraduates data handling using SPSS. It assumes no prior understanding beyond that... Læs mere
Doing Statistics With SPSS is derived from the authors' many years of experience teaching undergraduates data handling using SPSS. It assumes no prior understanding beyond that... Læs mere
This book is designed to teach beginners how to use SPSS, one of the most widely used computer package for analysing quantitative data.
A self-study guide to SPSS which contains screen dumps and exercises, glossary terms and worked examples. It covers a guide for learning how to use SPSS and a reference guide... Læs mere
This new edition of one of the most widely read textbooks in its field introduces the reader to data analysis with the most powerful and versatile statistical package on the market: IBM SPSS Statistics 19.
For courses on SPSS. SPSS is, essentially, a visually-driven program, but most texts rely primarily on a... Læs mere
This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its... Læs mere
A proven textbook based on materials developed over the last decade to teach linear, generalized, and mixed model analysis to students of ecology, evolution, and environmental studies. While R is used throughout, the focus is firmly on statistical analysis.