R Statistics Cookbook

The "R Statistics Cookbook" offers a comprehensive guide to solving statistical problems using R 3.5. Through over 100 practical recipes, you'll learn to perform essential statistical analyses, such as t-tests and regression, while mastering techniques for data modeling, nonparametric methods, and machine learning. This resource is tailored for tackling statistics-centric challenges across industries.

What this Book will help me do

• Confidently use R 3.5 to perform statistical analyses that meet your data needs.
• Apply various hypothesis testing methods, such as t-tests and ANOVA, effectively.
• Model and forecast data using time series analysis and mixed-effects modeling.
• Implement regression techniques, including Bayesian regression, for actionable insights.
• Leverage robust statistics and the caret package for machine learning applications in R.

Author(s)

None Juretig, a professional statistician and experienced educator, has an extensive background in applying statistical methods to real-world problems using R. Their writing combines deep technical knowledge with an approachable teaching style, making complex statistical concepts accessible to learners of varying levels.

Who is it for?

If you're a statistician, data scientist, researcher, or analyst with proficiency in R programming and foundational knowledge of linear algebra, this book is crafted for you. It caters to professionals looking to solidify their statistical knowledge while exploring practical, real-world applications. Whether seeking to apply advanced methods or refine your statistical approaches, this guide provides actionable insights.