A Practical Guide to Data Analysis Using R: An Example-Based Approach

This text examines the assumptions underlying data analysis models and provides practical intuition for scientists analyzing their own data. It covers topics such as cluster analysis, exponential time series, matching, seasonality, and resampling approaches, and includes worked examples and commentary to help readers recognize when a method works and when it doesn't. Selected solutions, notes, slides, and R code are available online, with extensive references to detailed guides to R.

Format: Hardback
Length: 550 pages
Publication date: 30 May 2024
Publisher: Cambridge University Press

This comprehensive text delves into the realm of data analysis, employing diverse real-world examples to elucidate its significance within a specific research context. It explores the underlying assumptions and methodologies employed in data analyses, offering insights into how these assumptions can be verified and assessed. Building upon the successful third edition of Data Analysis and Graphics Using R (Cambridge, 2010), this text expands its coverage to include topics such as cluster analysis, exponential time series, matching, seasonality, and resampling approaches. An in-depth examination of p-values leads to a discussion of replicability issues and the presence of multiple p-values in various contexts, including gene expression. By fostering practical intuition, this book empowers scientists to analyze their own data and familiarizes students with statistical theory through practical data analysis. Extensive worked examples and accompanying commentary guide readers in discerning the effectiveness of different methods, while a wealth of exercises and selected solutions, notes, slides, and R code are available online, accompanied by extensive references to detailed guides on R.

Weight: 1170g
Dimension: 250 x 176 x 35 (mm)
ISBN-13: 9781009282277