Statistical Inference for Data Science by Brian Caffo
Statistical Inference for Data Science - Table of Contents
- 1. Introduction
- 2. Principles of Probability
- 3. Foundations of Conditional Probability
- 4. Expected Values and Expectations
- 5. Measuring Variance and Variation
- 6. Properties of Some Common Distributions
- 7. Asymptopia and Limit Theorems
- 8. Constructing t Confidence Intervals
- 9. Principles of Hypothesis Testing
- 10. Interpreting P-values
- 11. Statistical Power Calculations
- 12. The Bootstrap and Resampling
What You Will Learn in Statistical Inference for Data Science
Statistical Inference for Data Science by Brian Caffo is an essential, highly practical textbook designed to give data practitioners a solid mathematical foundation in making conclusions from uncertain data. Developed as part of the renowned Johns Hopkins Data Science Specialization, this foundational text breaks down core inferential topics like conditional probability, likelihood, confidence intervals, hypothesis testing, p-values, power calculations, and bootstrap resampling into clear, step-by-step analytical lessons.
Perfect for undergraduate and graduate students in data science, biostatistics, computer science, and quantitative analytics, this book balances theoretical rigor with computational implementation in R. Professor Caffo systematically walks readers through the mechanics of drawing reliable inferences from sample data while avoiding common pitfalls in statistical decision-making. Whether calculating permutation tests or evaluating multiple comparison adjustments, learners will find this structured content invaluable.
Known for its concise explanation, pedagogical clarity, and focus on practical applications, it remains one of the best statistical inference for data science books pdf available for self-study. It systematically equips readers with essential analytical tools for mastering modern statistical inference with confidence.
Book Details & Specifications
Title:
Statistical Inference for Data Science by Brian Caffo
Publisher:
Leanpub
Year:
2016
Pages:
124
Type:
PDF
Language:
English
ISBN-10 #:
B07GNKYXNV
ISBN-13 #:
978-1316946688
License:
CC BY-NC-SA 4.0
Amazon:
Amazon
About the Author: Brian Caffo
The author Brian Caffo
is a Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He earned his Ph.D. in Statistics from the University of Florida and has received numerous teaching awards for his innovative approaches to online higher education.
Co-founder of the hugely successful Johns Hopkins Coursera Data Science Specialization, Professor Caffo has educated millions of learners globally. His research focuses on statistical computing, neuroimaging, and biostatistics, providing students worldwide with accessible, mathematically sound foundations for data-driven discovery.
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