Introductory Statistical Inference with the Likelihood Function

  • Charles A. Rohde

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Charles A. Rohde
    Pages 1-10
  3. Charles A. Rohde
    Pages 11-16
  4. Charles A. Rohde
    Pages 17-26
  5. Charles A. Rohde
    Pages 27-40
  6. Charles A. Rohde
    Pages 41-62
  7. Charles A. Rohde
    Pages 63-65
  8. Charles A. Rohde
    Pages 67-83
  9. Charles A. Rohde
    Pages 85-100
  10. Charles A. Rohde
    Pages 101-124
  11. Charles A. Rohde
    Pages 125-132
  12. Charles A. Rohde
    Pages 133-146
  13. Charles A. Rohde
    Pages 147-150
  14. Charles A. Rohde
    Pages 151-165
  15. Charles A. Rohde
    Pages 167-180
  16. Charles A. Rohde
    Pages 181-185
  17. Charles A. Rohde
    Pages 187-195
  18. Charles A. Rohde
    Pages 197-209
  19. Charles A. Rohde
    Pages 211-235
  20. Charles A. Rohde
    Pages 237-248

About this book

Introduction

This textbook covers the fundamentals of statistical inference and statistical theory including Bayesian and frequentist approaches and methodology possible without excessive emphasis on the underlying mathematics. This book is about some of the basic principles of statistics that are necessary to understand and evaluate methods for analyzing complex data sets. The likelihood function is used for pure likelihood inference throughout the book. There is also coverage of severity and finite population sampling. The material was developed from an introductory statistical theory course taught by the author at the Johns Hopkins University’s Department of Biostatistics. Students and instructors in public health programs will benefit from the likelihood modeling approach that is used throughout the text. This will also appeal to epidemiologists and psychometricians.  After a brief introduction, there are chapters on estimation, hypothesis testing, and maximum likelihood modeling. The book concludes with sections on Bayesian computation and inference. An appendix contains unique coverage of the interpretation of probability, and coverage of probability and mathematical concepts.

Keywords

Bayes' Theorem Biostatistics Bayesian Inference Biostatistics Methodology Likelihood Function Likelihood Modeling Pure Likelihood Inference Severity Statistical Inference for Biology

Authors and affiliations

  • Charles A. Rohde
    • 1
  1. 1.Bloomberg School of HealthJohns Hopkins UniversityBaltimoreUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-10461-4
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-10460-7
  • Online ISBN 978-3-319-10461-4
  • About this book