Statistics for Data Science: A Beginner-Friendly Guide to Concepts Code & Clarity

<p><b>Statistics for Data Science:</b> A Beginner-Friendly Guide to Concepts Code & Clarity</p><p><br/><b>Author:</b> Amrita Panjwani | Senior Data Scientist</p><p>&nbsp;<br/>Break into Data Science &mdash; with Confidence in Statistics.</p><p>Struggling with statistics while learning data science or machine learning? You&rsquo;re not alone &mdash; and this book is your solution. This is the ideal beginner-friendly guide to statistical thinking practical concepts and real-world code written for professionals students and non-technical learners stepping into data-driven careers.</p><p>&nbsp;<br/><b>What You&rsquo;ll Learn:</b><br/><b>Foundational topics:</b> distributions probability regression hypothesis testing<br/><b>Practical insights:</b> how real data scientists use stats in business decisions<br/><b>Code examples in Python</b> that make statistical concepts actionable<br/><b>Clarity-first approach:</b> visuals analogies and step-by-step breakdowns<br/>&nbsp;<br/><b>Why This Book Works:</b><br/>Designed specifically for beginners in data science AI or analytics<br/>Written in plain language by an experienced trainer and practitioner<br/>Blends theory application and business relevance<br/>Helps you connect the dots &mdash; from numbers to decisions<br/>&nbsp;<br/><b>Who Should Read This:</b><br/>Aspiring data scientists or analysts from non-technical backgrounds<br/>ML and AI learners struggling to understand the &ldquo;stats part&rdquo;<br/>Students preparing for interviews projects or coursework<br/>Professionals who want to upskill for data-informed roles<br/>&nbsp;<br/>Buy now and take the first step toward data science clarity.</p>