Encourages development of application and decision making skills for use in managing raw data and real-world projects. This book includes such topics as scattergrams and time series graphs, simple and multiple regressions, time series analysis, and random sampling.

aeo An encyclopaedic reference text for all aspects of advanced medical statistics aeo Special regression problems have been added to the new edition aeo ". the standard text for professional medical statisticians. " -- Aslib Book Guide aeo new chapter on laboratory assays.

Bayesian Essentials with R

Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS(R) Performing Data Analysis Using IBM SPSS(R) uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets.

"Preface This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics. Although introductory in its early sections, the book is definitely not elementary in the sense of a first text in statistics. The mathematics used in our book is basic probability and statistics, elementary calculus, and linear algebra. A review of probability notation is given in Chapter 1 along with a more detailed list of topics assumed to have been studied. The practical orientation of the book means that the reader's previous experience in probability, statistics, and linear algebra should ideally have included strong computational components. To write an introductory text alone would leave many readers with only a taste of the conceptual elements but no guidance for venturing into genuine practical applications, beyond those where Bayesian methods agree essentially with standard non-Bayesian analyses. On the other hand, we feel it would be a mistake to present the advanced methods without first introducing the basic concepts from our data-analytic perspective. Furthermore, due to the nature of applied statistics, a text on current Bayesian methodology would be incomplete without a variety of worked examples drawn from real applications. To avoid cluttering the main narrative, there are bibliographic notes at the end of each chapter and references at the end of the book"--

Walking the reader through the steps of statistical tests and providing data sets and screen shots from SPSS, this student-friendly book helps students to successfully use statistical tests in SPSS, interpret the results and also to understand statistical concepts.

The R version of Andy Field's hugely popular Discovering Statistics Using SPSS takes students on a journey of statistical discovery using the freeware R a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences.

A Practical Approach to using Multivariate Analyses Using Multivariate Statistics, 6th edition provides advanced undergraduate as well as graduate students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher-level mathematics.

Business Statistics using Excel offers a step-by-step guide to the theory and methodology behind the use of statistics in business. Integrated screenshots offer clear guidance through each Excel process and exercises are imbedded throughout each chapter to ensure that students engage with the content and frequently test their understanding.

Rev. ed. of: Computer-aided multivariate analysis. 4th ed. c2004.

In searching out the methodological principles on which grounded theory is built, the author reveals its main features as a qualitative research methodology for social research and the issues fundamental to understanding it. He also highlights the disagreements between the originators of grounded theory, their reasons, and their effects.

Written with those with limited mathematical and statistical knowledge in mind, this concise and practical guide helps researchers to do their research in new and alternative ways.

This fifth edition is appropriate for a one semester general course in Applied Statistics or as a reference book for practicing researchers in a wide variety of disciplines, including medicine, health and human services, natural and social sciences, law, and engineering.

This comprehensive second edition offers readers a complete guide to carrying out research projects involving structural equation modeling (SEM).

Provides advanced students with a comprehensive introduction to commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge of higher level mathematics. Each technique chapter: discusses tests for assumptions of analysis, presents a small example and describes varieties of analysis.

Everything a student needs to learn statistics starting from the basics and progressing onto sophisticated statistical modelling. A genuine one-off that uses humour, and the quirks of the everyday, to bring statistics to life and to make it accessible.

For the 1 or 2 semester course in Business Statistics. Emphasizing the use of statistical software like Excel and Minitab, this comprehensive text offers a rich array of business examples, real data, and a unique step-by-step framework that allows students to learn by doing.