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Introductory Statistical Inference with the Likelihood Function

  • Textbook
  • © 2014

Overview

Authors:
  1. Charles A. Rohde

    1. Bloomberg School of Health, Johns Hopkins University, Baltimore, USA

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  • Teaches the foundations of statistical theory through likelihood modeling, a vital approach to statistical theory that is possible with less emphasis on the mathematics
  • Perfect introductory text in biostatistics for students enrolled in doctoral and masters-level public health programs
  • Chapters use examples and exercises (with solutions provided) so the book can be used in class and for self-learning
  • Includes supplementary material: sn.pub/extras

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Table of contents (21 chapters)

  1. Front Matter

    Pages i-xvi
    Download chapter PDF

  2. Introduction

    • Charles A. Rohde
    Pages 1-10

  3. The Statistical Approach

    • Charles A. Rohde
    Pages 11-16

  4. Estimation

    • Charles A. Rohde
    Pages 17-26

  5. Interval Estimation

    • Charles A. Rohde
    Pages 27-40

  6. Hypothesis Testing

    • Charles A. Rohde
    Pages 41-62

  7. Standard Practice of Statistics

    • Charles A. Rohde
    Pages 63-65

  8. Maximum Likelihood: Basic Results

    • Charles A. Rohde
    Pages 67-83

  9. Linear Models

    • Charles A. Rohde
    Pages 85-100

  10. Other Estimation Methods

    • Charles A. Rohde
    Pages 101-124

  11. Decision Theory

    • Charles A. Rohde
    Pages 125-132

  12. Sufficiency

    • Charles A. Rohde
    Pages 133-146

  13. Conditionality

    • Charles A. Rohde
    Pages 147-150

  14. Statistical Principles

    • Charles A. Rohde
    Pages 151-165

  15. Bayesian Inference

    • Charles A. Rohde
    Pages 167-180

  16. Bayesian Statistics: Computation

    • Charles A. Rohde
    Pages 181-185

  17. Bayesian Inference: Miscellaneous

    • Charles A. Rohde
    Pages 187-195

  18. Pure Likelihood Methods

    • Charles A. Rohde
    Pages 197-209

  19. Pure Likelihood Methods and Nuisance Parameters

    • Charles A. Rohde
    Pages 211-235

  20. Other Inference Methods and Concepts

    • Charles A. Rohde
    Pages 237-248
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Keywords

About this book

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.

Authors and Affiliations

  • Bloomberg School of Health, Johns Hopkins University, Baltimore, USA

    Charles A. Rohde

About the author

Charles A. Rohde received his PhD at N.C. State in 1964 and has been at Johns Hopkins since then. He served as Department Chair for the Department of Biostatistics from 1981 to 1996. Professor Rohde's areas of research have included generalized inverses of matrices, linear models and pure likelihood methods.

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