AI-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python Edition: 3

Statistical methods are a key part of AI and data science, yet few data scientists have formal statistical training. The third edition of this popular guide expands its practical foundations in R and Python into the modern AI toolkit, with new chapters on neural networks, deep learning, and large language models. Generative AI is integrated throughout, showing how tools such as ChatGPT, Claude, and Gemini work, and how they can support real-world statistical workflows. This book highlights concepts that matter most when working with data, building predictive models, and deploying AI responsibly. If you’re comfortable with R or Python and have had some exposure to basic statistics, this concise reference will boost your statistical literacy, your understanding of how AI works, and your confidence in real-world data science and AI projects. • Conduct exploratory data analysis to improve models • Apply sampling and experimental design to reduce bias and answer [...]questions with clarity • Use regression to understand data-generating processes and detect anomalies • Build predictive models using classification, clustering, and unsupervised learning with unbalanced data • Understand how generative AI works, and use tools like ChatGPT, Claude, and Gemini to help you analyze data and build machine learning models