Table of Contents
My new book on Applied Statistics for Data Science is organized into three major parts as follows:
Part I: Foundations
- Chapter 1: Random Events, Variables & Probability Modeling
- Chapter 2: Distribution Families & Shapes
- Chapter 3: Sampling & Estimators
Part II: Core Statistical Tools
- Chapter 4: Hypothesis Testing & Statistical Comparison Methods
- Chapter 5: Regression & Prediction Diagnostics
- Chapter 6: Sampling Designs & Experiments
- Chapter 7: Resampling & Permutation Based Inference
Part III: Drift, Reliability & Temporal Behavior
- Chapter 8: Nonparametric Drift Detection & Monitoring
- Chapter 9: Parametric Drift Detection & Monitoring
- Chapter 10: Survival Curves & Reliability Modeling
Who Should Read This Book?
- Data scientists and machine learning practitioners who want stronger intuition behind the tools they use every day.
- Engineers and analysts who evaluate models, design experiments, or monitor systems in production.
- Researchers, students and curious enthusiasts who want a practical bridge between mathematical statistics and applied machine learning.
- Professionals in reliability, operations, or risk modeling who need to understand drift, survival curves, and temporal behavior through simple explanations and practical examples.
You do not need an advanced math background. Curiosity and a willingness to explore ideas through examples and simulation are enough.
Meet the Author
Gal Arav
Data Scientist, INstructor & Consultant
Gal Arav bridges classical statistics and modern data science.
His work focuses on making statistical theory practical for real‑world applications, combining clear mathematical understanding with hands‑on Python expertise. His new book reflects a commitment to accuracy and clarity.
Gal has led machine‑learning and analytics projects at NASA, Google, Verizon, AT&T, and General Motors. Gal previously founded an internet‑based market research company featured in Barron’s and Bloomberg Businessweek and worked as a quantitative researcher in global currency markets.
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Consulting & Technical Training Services
In today’s increasingly complex world of artificial intelligence & machine learning, data practitioners must develop a strong statistical toolbox to properly manage, monitor, and understand the behavior of these systems.
You’re welcome to connect with me on LinkedIn if you’re interested in consulting work or if you’d like to book practical, focused training sessions for your technical team. I offer instructional courses at different levels, all come with complete documentation and detailed Google Colab notebooks in Python that accompany each course.
1. Applied Statistics - Foundations
2. Applied Statistics - Intermediate
3. Applied Statistics - Advanced
My Upcoming Books
Two books.
One complementary picture of modern data science.
Coming Soon
Applied Statistics
for Data Science
Essential methods for data practitioners, from theory to practice, with accompanying Python notebooks in GitHub
A Short History of
Probability and Statistics
From dice games to advanced statistics, the 400-year story behind the rise of Machine Learning.
contact me
Questions, feedback, or just want to say hello?
or
https://www.linkedin.com/in/galarav