Modern Data Science with r

2 min readJun 20, 2024

“Modern Data Science with R” is a comprehensive textbook for undergraduates that teaches data science using the R programming language and RStudio environment. The book emphasizes a modern approach to data science, incorporating statistical and computational thinking to solve real-world problems with data.

Key Features:

Focus on Real-World Problems: The book emphasizes using R to tackle real-world data problems, making it practical and relevant.
Statistical and Computational Thinking: It integrates statistical concepts with computational skills, teaching students how to think critically about data and use R effectively.
Updated for Tidyverse: The second edition reflects the growing popularity and influence of the tidyverse set of packages, which provide a consistent and efficient way to work with data in R.
Comprehensive Coverage: The book covers various topics, from data wrangling and visualization to statistical modeling and machine learning.
Accessible for Undergraduates: It’s designed for undergraduate students, making it approachable and engaging for beginners in data science.

Content Overview:

Introduction: Introduces data science, R, and RStudio, setting the foundation for the rest of the book.
Data Visualization: Teaches students how to create compelling visualizations using ggplot2, a powerful R package.
Tidy Data emphasizes the importance of tidy data principles and how to work with data consistently and efficiently using tidyverse packages.
Data Wrangling: Covers data cleaning, transformation, and manipulation using dplyr, tidyr, and other tidyverse tools.
Statistical Modeling: Introduces statistical concepts and models, such as linear regression, logistic regression, and generalized linear models, and demonstrates how to implement them in R.
Machine Learning: This chapter explores various machine learning algorithms, including decision trees, random forests, and clustering, and shows how to use them for prediction and classification tasks.
Communication: Stresses the importance of communicating results effectively, using clear writing, visualizations, and presentations.