Probability Theory and Statistics with Real World Applications
Univariate and Multivariate Models Applications
- 370 pages
- English
- ePUB (mobile friendly)
- Only available on web
Probability Theory and Statistics with Real World Applications
Univariate and Multivariate Models Applications
About This Book
The idea of the book is to present a text that is useful for both students of quantitative sciences and practitioners who work with univariate or multivariate probabilistic models. Since the text should also be suitable for self-study, excessive formalism is avoided though mathematical rigor is retained. A deeper insight into the topics is provided by detailed examples and illustrations. The book covers the standard content of a course in probability and statistics. However, the second edition includes two new chapters about distribution theory and exploratory data analysis. The first-mentioned chapter certainly goes beyond the standard material. It is presented to reflect the growing practical importance of developing new distributions. The second new chapter studies intensively one- and bidimensional concepts like assymetry, kurtosis, correlation and determination coefficients. In particular, examples are intended to enable the reader to take a critical look at the appropriateness of the geometrically motivated concepts.
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Table of contents
- Title Page
- Copyright
- Contents
- 1 Mathematics revision
- 2 Introduction to probability
- 3 Finite sample spaces
- 4 Conditional probability and independence
- 5 One-dimensional random variables
- 6 Functions of random variables
- 7 Bidimensional random variables
- 8 Characteristics of random variables
- 9 Discrete probability models
- 10 Continuous probability models
- 11 Generating functions in probability
- 12 Construction of new distributions
- 13 Sums of many random variables
- 14 Samples and sampling distributions
- 15 Estimation of parameters
- 16 Hypothesis tests
- 17 Exploratory data analysis
- Index