Andrew Bruce Bücher

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this practical guide-now including examples in Python as well as R-explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data scientists use statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages, and have had some exposure to statistics but want to learn more, this quick reference bridges the gap in an accessible, readable format. With this updated edition, you'll dive into: Exploratory data analysis Data and sampling distributions Statistical experiments and significance testing Regression and prediction Classification Statistical machine learning Unsupervised learning

With case studies, practical exercises and self-tests, this text enables managers to master their organisation and respond in a timely way to new demands

Exploring the struggles of pornography addiction, this book provides an emotional, physical, and mental journey aimed at Christians seeking liberation from such challenges. It emphasizes the transformative power of faith in Christ Jesus, offering hope and guidance for those yearning for freedom. Through personal insights and spiritual encouragement, it serves as a resource for individuals on their path to recovery and a deeper relationship with their faith.