The book is intended for specialists in the field of Data Science who have some experience with the R programming language and have a preliminary understanding of mathematical statistics. It introduces key concepts from statistics that relate to data science in a convenient and easily accessible way, and explains which concepts are important and useful from a data science perspective, which are less important, and why. Topics covered in detail include: exploratory data analysis, data and sample distributions, statistical experiments and significance testing, regression and prediction, classification, statistical machine learning and unsupervised learning. The second edition includes examples in Python, which expands the practical application of the book.

After reading this book, you will learn:

You will master: