Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly.

Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples.

Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility.

This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst.

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Spis treści

Data Analysis with R. A comprehensive guide to manipulating, analyzing, and visualizing data in R - Second Edition eBook -- spis treści

• 1. RefresheR
• 2. The Shape of Data
• 3. Describing Relationships
• 4. Probability
• 5. Using Data to Reason about the World
• 6. Testing Hypotheses
• 7. Bayesian Methods
• 8. The Bootstrap
• 9. Predicting Continuous Variables
• 10. Predicting Categorical Variables
• 11. Predicting Changes with Time
• 12. Sources Of Data
• 13. Dealing with Missing Data
• 14. Dealing with Messy Data
• 15. Dealing with Large Data
• 16. Working with Popular R Packages
• 17. Reproducibility and Best Practices