Practical Statistics for Data Scientists

This book is a must-have for aspiring data scientists who lack formal statistical training. It explores statistical methods from a data science perspective and provides practical guidance on their application. The second edition includes comprehensive examples in Python and advice on avoiding their misuse. You'll learn all about exploratory data analysis, random sampling, experimental design, regression, and more. Plus, the book covers unsupervised learning methods for extracting meaning from unlabeled data. If you're familiar with R or Python and have some exposure to statistics, this accessible reference will bridge the gap for you.