The A-Z of Error-Free Research

by Philip Good

A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R Code The A–Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical trials, and surveys. The book shows you when to use statistics, the best ways to cope with variation, and how to design an experiment, determine optimal sample size, and collect useable data. It also helps you choose the best statistical procedures for your application and takes you step by step through model development and reporting results for publication. Transition from Student to Researcher Helping you become a confident researcher, the book begins with an overview of when―and when not―to use statistics. It guides you through the planning and data collection phases and presents various data analysis techniques, including methods for sample size determination. The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure your research efforts get the proper credit. The book concludes with case-control and cohort studies.

270 pages, Paperback

First published August 20, 2012

Reviews

[Tom Schulte · Rating 3 out of 5]

“A-Z” suggests a breadth of completeness probably not possible in roughly 240 pages. The subtitle on the back is both more detailed and more accurate for this ABCs (and R) of applied statistics in research: “A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R Code”. R is a free programming language and environment for statistical computing. The R language is widely used among statisticians. R's popularity has increased substantially in recent years. This book follows a similar trend: R content increases exponentially as the page numbers rise. Final material includes an R primer and function index. Being conversant in R, and probably planning to use R in research, is a prerequisite to maximizing usage of this book. Understanding and embracing R is implicit and basically taken for granted throughout, although there are pointers.

(See my full review on MathDL: MAA Reviews.)