Regression Analysis with R

Dive into the world of regression analysis with this hands-on guide that covers everything you need to know about building effective regression models in R. You'll learn both the theoretical foundations and how to apply them using practical examples and R code. By the end, you'll be equipped to interpret regression results and use them to make meaningful predictions.

What this Book will help me do

• Master the fundamentals of regression analysis, from simple linear to logistic regression.
• Gain expertise in R programming for implementing regression models and analyzing results.
• Develop skills in handling missing data, feature engineering, and exploratory data analysis.
• Understand how to identify, prevent, and address overfitting and underfitting issues in modeling.
• Apply regression techniques in real-world applications, including classification problems and advanced methods like Bagging and Boosting.

Author(s)

Giuseppe Ciaburro is an experienced data scientist and author with a passion for making complex technical topics accessible. With expertise in R programming and regression analysis, he has worked extensively in statistical modeling and data exploration. Giuseppe's writing combines clear explanations of theory with hands-on examples, ideal for learners and practitioners alike.

Who is it for?

This book is perfect for aspiring data scientists and analysts eager to understand and apply regression analysis using R. It's suited for readers with a foundational knowledge of statistics and basic R programming experience. Whether you're delving into data science or aiming to strengthen existing skills, this book offers practical insights to reach your goals.