A Practical Guide to Data Analysis Using R
Language: English
Published by Cambridge University Press, GB, 2024
- Hardcover
- New

Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
AbeBooks seller since June 11, 2025
Condition: New
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Add to basketItem description from seller
Using diverse real-world examples, this text examines what models used for data analysis mean in a specific research context. What assumptions underlie analyses, and how can you check them? Building on the successful 'Data Analysis and Graphics Using R,' 3rd edition (Cambridge, 2010), it expands upon topics including cluster analysis, exponential time series, matching, seasonality, and resampling approaches. An extended look at p-values leads to an exploration of replicability issues and of contexts where numerous p-values exist, including gene expression. Developing practical intuition, this book assists scientists in the analysis of their own data, and familiarizes students in statistical theory with practical data analysis. The worked examples and accompanying commentary teach readers to recognize when a method works and, more importantly, when it doesn't. Each chapter contains copious exercises. Selected solutions, notes, slides, and R code are available online, with extensive references pointing to detailed guides to R.…
Seller Inventory # LU-9781009282277
- Title
- A Practical Guide to Data Analysis Using R
- Author
- John H. Maindonald, W. John Braun, Jeffrey L. Andrews
- Publisher
- Cambridge University Press, GB
- Publication year
- 2024
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1009282271
- ISBN 13
- 9781009282277
- Item weight
- 1,160 grams
"Synopsis" may belong to another edition of this title.
About the Author
W. John Braun is Professor at the University of British Columbia, where he is Director of the UBCO campus of the Banff International Research Station for Mathematical Innovation and Discovery. In 2020, he received the Statistical Society of Canada Award for Impact of Applied and Collaborative Work.
Jeffrey Andrews is Associate Professor at the University of British Columbia. He currently serves as Principal Co-director of the Master of Data Science program and President-elect of The Classification Society (TCS). He is the 2013 Distinguished Dissertation Award winner from TCS and a recipient of the 2017 Chikio Hayashi Award for Young Researchers from the International Federation of Classification Societies.
"About the title" may belong to another edition of this title.
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