Understanding Advanced Statistical Methods
eBook - PDF

Understanding Advanced Statistical Methods

  1. 569 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Understanding Advanced Statistical Methods

Book details
Table of contents
Citations

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

Publisher
Chapman and Hall/CRC
Year
2013
ISBN
9781466512115
Edition
1
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Front Cover
  2. Contents
  3. List of Examples
  4. Preface
  5. Acknowledgments
  6. Authors
  7. Chapter 1. Introduction: Probability, Statistics, and Science
  8. Chapter 2. Random Variables and Their Probability Distributions
  9. Chapter 3. Probability Calculation and Simulation
  10. Chapter 4. Identifying Distributions
  11. Chapter 5. Conditional Distributions and Independence
  12. Chapter 6. Marginal Distributions, Joint Distributions, Independence, and Bayes’ Theorem
  13. Chapter 7. Sampling from Populations and Processes
  14. Chapter 8. Expected Value and the Law of Large Numbers
  15. Chapter 9. Functions of Random Variables: Their Distributions and Expected Values
  16. Chapter 10. Distributions of Totals
  17. Chapter 11. Estimation: Unbiasedness, Consistency, and Efficiency
  18. Chapter 12. Likelihood Function and Maximum Likelihood Estimates
  19. Chapter 13. Bayesian Statistics
  20. Chapter 14. Frequentist Statistical Methods
  21. Chapter 15. Are Your Results Explainable by Chance Alone?
  22. Chapter 16. Chi-Squared, Student’s t, and F-Distributions, with Applications
  23. Chapter 17. Likelihood Ratio Tests
  24. Chapter 18. Sample Size and Power
  25. Chapter 19. Robustness and Nonparametric Methods
  26. Chapter 20. Final Words
  27. Index
  28. Back Cover