Statistics for Data Science

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.