Nina Zumel Bücher

Practical Data Science with R effectively explains essential principles without unnecessary theory, focusing on real-world applications in data collection, curation, and analysis vital for business success. It utilizes the R programming language and statistical techniques through well-explained examples in marketing, business intelligence, and decision support. As business analysts and developers increasingly engage with crucial data, the R language offers a straightforward approach to everyday data science tasks, minimizing the need for complex mathematics. This resource demonstrates how to apply R and relevant statistical methods to common business scenarios, including designing experiments like A/B tests, building predictive models, and presenting results effectively to diverse audiences. The book is designed for readers with no prior data science background, though some familiarity with basic statistics, R, or another scripting language is beneficial. Key topics include data science for professionals, statistical analysis using R, project lifecycle from planning to delivery, relatable use cases, and effective data presentation strategies.