It seems that most introductory R books spend too much time with correlations and other modeling. I am still hoping to find an R book that deals primarily with data manipulation and descriptive graphics at an intro to intermediate level. Simply put, knowing something well and conveying it properly
A Practical Guide to Data Analysis Using R: An Example-Based Approach
โ Scribed by John H. Maindonald, W. John Braun, Jeffrey L. Andrews
- Publisher
- Cambridge University Press
- Year
- 2024
- Tongue
- English
- Leaves
- 551
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
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