Principles of Statistical Analysis: Learning from Randomized Experiments

ISBN-13: 9781108489676 / Angielski / Twarda / 2022 / 400 str.

San Diego) Arias-Castro Ery (University of California

Opis

This concise course in data analysis and inference for the mathematically literate builds on survey sampling and designed experiments.

Recenzje

'This text is highly recommended for undergraduate students wanting to grasp the key ideas of modern data analysis. Arias-Castro achieves something that is rare in the art of teaching statistical science - he uses mathematical language in an intelligible and highly helpful way, without surrendering key intuitions of statistics to formalism and proof. In this way, the reader can get through an impressive amount of material without, however, ever getting into muddy waters.' Richard Nickl, Statistical Laboratory, Cambridge University

Spis treści

Preface; Acknowledgments; Part I. Elements of Probability Theory: 1. Axioms of probability theory; 2. Discrete probability spaces; 3. Distributions on the real line; 4. Discrete distributions; 5. Continuous distributions; 6. Multivariate distributions; 7. Expectation and concentration; 8. Convergence of random variables; 9. Stochastic processes; Part II. Practical Considerations: 10. Sampling and simulation; 11. Data collection; Part III. Elements of Statistical Inference: 12. Models, estimators, and tests; 13. Properties of estimators and tests; 14. One proportion; 15. Multiple proportions; 16. One numerical sample; 17. Multiple numerical samples; 18. Multiple paired numerical samples; 19. Correlation analysis; 20. Multiple testing; 21. Regression analysis; 22. Foundational issues; References; Index.