Probability Theory and Statistical Applications
eBook - PDF

Probability Theory and Statistical Applications

  1. 293 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Probability Theory and Statistical Applications

Book details
Table of contents
Citations

About This Book

This accessible and easy-to-read book provides many examples to illustrate diverse topics in probability and statistics, from initial concepts up to advanced calculations. Special attention is devoted e.g. to independency of events, inequalities in probability and functions of random variables. The book is directed to students of mathematics, statistics, engineering, and other quantitative sciences, in particular to readers who need or want to learn by self-study. The author is convinced that sophisticated examples are more useful for the student than a lengthy formalism treating the greatest possible generality.

Contents:
Mathematics revision
Introduction to probability
Finite sample spaces
Conditional probability and independence
One-dimensional random variables
Functions of random variables
Bi-dimensional random variables
Characteristics of random variables
Discrete probability models
Continuous probability models
Generating functions in probability
Sums of many random variables
Samples and sampling distributions
Estimation of parameters
Hypothesis tests

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Yes, you can access Probability Theory and Statistical Applications by Peter Zörnig 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
De Gruyter
Year
2016
ISBN
9783110402711
Edition
1
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Preface
  2. Contents
  3. 1 Mathematics revision
  4. 2 Introduction to probability
  5. 3 Finite sample spaces
  6. 4 Conditional probability and independence
  7. 5 One-dimensional random variables
  8. 6 Functions of random variables
  9. 7 Bi-dimensional random variables
  10. 8 Characteristics of random variables
  11. 9 Discrete probability models
  12. 10 Continuous probability models
  13. 11 Generating functions in probability
  14. 12 Sums of many random variables
  15. 13 Samples and sampling distributions
  16. 14 Estimation of parameters
  17. 15 Hypothesis tests
  18. Appendix
  19. References
  20. Index