{"product_id":"statistics-for-data-science-and-ai-9798187997480","title":"Statistics For Data Science and AI","description":"\u003cp\u003e • Author(s): Rashmi Patel\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Computer Science\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eStatistics for Data Science: Complete Reference\u003c\/b\u003e is a comprehensive, practical handbook designed for data scientists, machine learning engineers, AI practitioners, software developers, researchers, and students who want to master statistics through real-world applications and Python programming.\u003c\/p\u003e\u003cp\u003eModern data science is built on statistics. Every machine learning model, A\/B test, forecasting system, recommendation engine, and AI application depends on sound statistical principles. This book bridges mathematical concepts with practical implementation, enabling readers to confidently analyze data, build predictive models, and make evidence-based decisions.\u003c\/p\u003e\u003cp\u003eUnlike traditional statistics textbooks that emphasize theory alone, this reference combines intuitive explanations, mathematical foundations, production-oriented guidance, and complete Python implementations using industry-standard libraries.\u003c\/p\u003e\u003cp\u003eInside you'll learn: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eStatistical foundations, data types, sampling methods, and exploratory data analysis (EDA)\u003c\/li\u003e\n\u003cli\u003eDescriptive statistics, probability theory, probability distributions, and statistical inference\u003c\/li\u003e\n\u003cli\u003eConfidence intervals, hypothesis testing, statistical significance, and effect size analysis\u003c\/li\u003e\n\u003cli\u003eLinear regression, logistic regression, multicollinearity, diagnostics, and model validation\u003c\/li\u003e\n\u003cli\u003eBayesian statistics, Bayesian inference, MCMC, and probabilistic modeling with PyMC\u003c\/li\u003e\n\u003cli\u003eTime series analysis, forecasting techniques, ARIMA, SARIMA, and stationarity testing\u003c\/li\u003e\n\u003cli\u003eA\/B testing, experimental design, power analysis, sequential testing, and causal thinking\u003c\/li\u003e\n\u003cli\u003eNon-parametric statistics, bootstrap methods, permutation tests, and robust statistical techniques\u003c\/li\u003e\n\u003cli\u003eMultivariate analysis including PCA, factor analysis, clustering, and dimensionality reduction\u003c\/li\u003e\n\u003cli\u003eStatistical learning concepts, bias-variance tradeoff, cross-validation, feature selection, and model evaluation\u003c\/li\u003e\n\u003cli\u003eStatistical visualization using Matplotlib, Seaborn, Plotly, and best practices for communicating insights\u003c\/li\u003e\n\u003cli\u003eComplete Python examples using NumPy, Pandas, SciPy, Statsmodels, Scikit-learn, and PyMC\u003c\/li\u003e\n\u003cli\u003eInterview-focused questions, practical case studies, troubleshooting guidance, and a comprehensive statistical glossary\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eWhether you're preparing for data science interviews, building machine learning models, conducting business analytics, performing scientific research, or strengthening your statistical foundation for AI, this book provides the practical knowledge needed to apply statistics with confidence.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eStatistics for Data Science: Complete Reference\u003c\/b\u003e is an essential desktop reference that you'll return to throughout your career in data science, machine learning, and artificial intelligence. It covers the complete statistical toolkit required by modern AI professionals while emphasizing practical implementation over abstract theory.\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":48216015405207,"sku":"9798187997480","price":1771.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798187997480.webp?v=1788735374","url":"https:\/\/atlanticbooks.com\/products\/statistics-for-data-science-and-ai-9798187997480","provider":"Atlantic Books","version":"1.0","type":"link"}