- 569 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Understanding Advanced Statistical Methods
About this book
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum likelihood, bootstrapping, nonparametrics, and Bayesian me
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Yes, you can access Understanding Advanced Statistical Methods by Peter Westfall,Kevin S. S. Henning in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Front Cover
- Contents
- List of Examples
- Preface
- Acknowledgments
- Authors
- Chapter 1. Introduction: Probability, Statistics, and Science
- Chapter 2. Random Variables and Their Probability Distributions
- Chapter 3. Probability Calculation and Simulation
- Chapter 4. Identifying Distributions
- Chapter 5. Conditional Distributions and Independence
- Chapter 6. Marginal Distributions, Joint Distributions, Independence, and Bayes’ Theorem
- Chapter 7. Sampling from Populations and Processes
- Chapter 8. Expected Value and the Law of Large Numbers
- Chapter 9. Functions of Random Variables: Their Distributions and Expected Values
- Chapter 10. Distributions of Totals
- Chapter 11. Estimation: Unbiasedness, Consistency, and Efficiency
- Chapter 12. Likelihood Function and Maximum Likelihood Estimates
- Chapter 13. Bayesian Statistics
- Chapter 14. Frequentist Statistical Methods
- Chapter 15. Are Your Results Explainable by Chance Alone?
- Chapter 16. Chi-Squared, Student’s t, and F-Distributions, with Applications
- Chapter 17. Likelihood Ratio Tests
- Chapter 18. Sample Size and Power
- Chapter 19. Robustness and Nonparametric Methods
- Chapter 20. Final Words
- Index
- Back Cover