{"product_id":"practical-statistics-for-data-scientists-50-essential-concepts-using-r-and-python","title":"Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python","description":"\u003ch4\u003ePractical Statistics for Data Scientists\u003c\/h4\u003e\n\u003ch4\u003eMaster the Statistics That Matter in Data Science\u003c\/h4\u003e\n\u003cp\u003eStatistical knowledge is essential for effective \u003cstrong\u003edata science\u003c\/strong\u003e, yet many data scientists never receive formal training in statistics. Traditional statistics books often focus on theory, while many data science resources use statistical techniques without providing enough statistical context.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePractical Statistics for Data Scientists\u003c\/em\u003e\u003c\/strong\u003e bridges that gap.\u003c\/p\u003e\n\u003cp\u003eThe second edition delivers an accessible, practical guide to \u003cstrong\u003estatistics for data science\u003c\/strong\u003e, combining statistical concepts with real-world applications and comprehensive examples in \u003cstrong\u003ePython\u003c\/strong\u003e. You'll learn not only how statistical methods work, but also when to use them, how to interpret the results, and how to avoid common mistakes and misuse.\u003c\/p\u003e\n\u003cp\u003eWhether you're working with data professionally or building your skills in data analytics and machine learning, this book helps you focus on \u003cstrong\u003ewhat matters most—and what doesn't\u003c\/strong\u003e.\u003c\/p\u003e\n\u003ch2\u003eWhat You'll Learn\u003c\/h2\u003e\n\u003cp\u003eInside this practical statistics guide, you'll discover how to:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eUse exploratory data analysis (EDA)\u003c\/strong\u003e as a critical first step in understanding data\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eApply random sampling\u003c\/strong\u003e to reduce bias and create higher-quality datasets—even when working with big data\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eUnderstand experimental design\u003c\/strong\u003e and use it to answer important questions with greater confidence\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eApply regression techniques\u003c\/strong\u003e to estimate outcomes, identify relationships, and detect anomalies\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eUse classification methods\u003c\/strong\u003e to predict which categories or groups records belong to\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eUnderstand statistical machine learning\u003c\/strong\u003e techniques that learn patterns from data\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eApply unsupervised learning\u003c\/strong\u003e to discover useful patterns and meaning in unlabeled datasets\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eAvoid common statistical mistakes\u003c\/strong\u003e that can lead to misleading conclusions\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eConnect statistical concepts with practical data science workflows\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eBuilt for Modern Data Scientists\u003c\/h2\u003e\n\u003cp\u003eIf you're already familiar with \u003cstrong\u003ePython or R\u003c\/strong\u003e and have some basic exposure to statistics, this book provides the practical bridge between statistical theory and real-world data science.\u003c\/p\u003e\n\u003cp\u003eInstead of overwhelming you with unnecessary mathematical detail, it focuses on the statistical concepts and techniques you'll actually encounter when \u003cstrong\u003eanalyzing data, building models, interpreting results, and making data-driven decisions\u003c\/strong\u003e.\u003c\/p\u003e\n\u003ch3\u003eWhy Add This Book to Your Data Science Library?\u003c\/h3\u003e\n\u003cp\u003e✔ Practical statistics explained from a \u003cstrong\u003edata science perspective\u003c\/strong\u003e\u003cbr\u003e✔ Comprehensive \u003cstrong\u003ePython examples\u003c\/strong\u003e\u003cbr\u003e✔ Guidance on applying statistical methods correctly\u003cbr\u003e✔ Coverage of \u003cstrong\u003eregression, classification, sampling, experimental design, and machine learning\u003c\/strong\u003e\u003cbr\u003e✔ Helps you recognize and avoid statistical misuse\u003cbr\u003e✔ Ideal for \u003cstrong\u003edata scientists, analysts, programmers, and machine learning practitioners\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eBuild stronger statistical intuition. Analyze data with greater confidence. And learn the statistical methods that truly matter in modern data science.\u003c\/strong\u003e\u003c\/p\u003e\n\u003ch2\u003eProduct details\u003c\/h2\u003e\n\u003cdiv id=\"detailBullets_feature_div\"\u003e\n\u003cul class=\"a-unordered-list a-nostyle a-vertical a-spacing-none detail-bullet-list\"\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003ePublisher ‏ : ‎ \u003c\/span\u003e\u003cspan\u003eO'Reilly Media\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003ePublication date ‏ : ‎ \u003c\/span\u003e\u003cspan\u003eJune 16, 2020\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eEdition ‏ : ‎ \u003c\/span\u003e\u003cspan\u003e2nd\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eLanguage ‏ : ‎ \u003c\/span\u003e\u003cspan\u003eEnglish\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003ePrint length ‏ : ‎ \u003c\/span\u003e\u003cspan\u003e360 pages\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eISBN-10 ‏ : ‎ \u003c\/span\u003e\u003cspan\u003e149207294X\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eISBN-13 ‏ : ‎ \u003c\/span\u003e\u003cspan\u003e978-1492072942\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eItem Weight ‏ : ‎ \u003c\/span\u003e\u003cspan\u003e1.35 pounds\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cspan class=\"a-list-item\"\u003e\u003cspan class=\"a-text-bold\"\u003eDimensions ‏ : ‎ \u003c\/span\u003e\u003cspan\u003e7 x 0.9 x 9.1 inches\u003c\/span\u003e\u003c\/span\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e","brand":"thebookstella.com","offers":[{"title":"Default Title","offer_id":67233008517369,"sku":null,"price":66.89,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0840\/6948\/2745\/files\/PracticalStatisticsforDataScientists.jpg?v=1790548428","url":"https:\/\/thebookscharm.com\/products\/practical-statistics-for-data-scientists-50-essential-concepts-using-r-and-python","provider":"My Store","version":"1.0","type":"link"}