
- English
- PDF
- Available on iOS & Android
About this book
This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance – simulation and sampling, as well as experimental design and data collection – that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.
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Information
Table of contents
- Cover
- Half-title
- Endorsements
- Series information
- Title page
- Copyright information
- Dedication
- Epigraph
- Contents
- Preface
- Acknowledgements
- Part I Elements of Probability Theory
- Part II Practical Considerations
- Part III Elements of Statistical Inference
- References
- Index
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