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Statistics for Data Science: A Beginner-Friendly Guide to Concepts, Code & Clarity
Author: Amrita Panjwani Senior Data Scientist
Break into Data Science - with Confidence in Statistics.
Struggling with statistics while learning data science or machine learning? You're not alone - 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.
What You'll Learn:
Foundational topics: distributions, probability, regression, hypothesis testing
Practical insights: how real data scientists use stats in business decisions
Code examples in Python that make statistical concepts actionable
Clarity-first approach: visuals, analogies, and step-by-step breakdowns
Why This Book Works:
Designed specifically for beginners in data science, AI, or analytics
Written in plain language by an experienced trainer and practitioner
Blends theory, application, and business relevance
Helps you connect the dots - from numbers to decisions
Who Should Read This:
Aspiring data scientists or analysts from non-technical backgrounds
ML and AI learners struggling to understand the "stats part"
Students preparing for interviews, projects, or coursework
Professionals who want to upskill for data-informed roles
Buy now and take the first step toward data science clarity.
