Clear. Practical. Surprisingly enjoyable. This is not your average statistics textbook. No equations. No intimidating math. Just a refreshingly simple, visual, and concept-driven guide for researchers who want to make sense of their data. Whether you're a student, scientist, entrepreneur, or just data-curious, this book gives you the tools to: • Follow a proven 4-step framework for analyzing any dataset • Understand statistical terms in plain language • Learn through diagrams, screenshots, and real-world examples Perfect for those who crave clarity over complexity, this book turns data analysis into a creative and rewarding process. From spotting patterns to selecting statistical tests, you'll learn how to explore your data like a detective, and present your findings with confidence. No prior experience required. For survey results, business metrics, and scientific data, you'll gain practical skills that translate into real insights. About the Author: Dr. Jawad Hashim is a senior researcher, professor, and biostatistician with over 20 years of experience. A pioneer in the field and inventor of the e-value, a new metric for effect size, he ranks among the top 2% of most cited scientists worldwide. His hands-on workshops and award-winning teaching style have helped hundreds of students and professionals master the art of data analysis. Data doesn’t have to be daunting. With this book, it becomes your most powerful decision-making tool. CONTENTS DATA PREPARATION Data Data coding Data entry Missing values Data types Outcome and predictor variables Grouped variables Computed variables Before-after data GRAPHS AND CHARTS Bar charts Histograms Boxplots Scatterplots Well-designed charts Pitfalls BASIC STATISTICS Frequencies Averages Spread Correlation Compare two groups Confidence intervals ADVANCED STATISTICS Overview of statistical tests Compare three or more groups Before-after studies Linear regression Binary logistic regression Count regression Survival analysis Questionnaire reliability Test accuracy Bayesian analysis Small samples Sample size estimation Data science APPENDICES Statistical terms Statistical software Workflow Presenting test results Articles Books Websites Online data analysis Courses Artificial intelligence Mistakes and pitfalls Teaching statistics Quiz 1 – essentials Quiz 2 – advanced Case studies Simulations