This book provides a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation. It presents a detailed explanation of different distribution concepts used in statistics along with their application in real-life situations. Covering the analytical aspects using the latest software, the volume discusses stochastic methods and other statistical methods. It provides an overview of statistical data analysis by taking actual situations and implementing open-source software R version 4.0 and Python 3.0+. A detailed study of the statistical models is also provided with examples related to health, agriculture, insurance, and other sectors. Discusses the distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation. It discusses stochastic methods and other statistical methods and shows multiple actual situations using the open-source software R version 4.0 and Python 3.0+.
Cover 1
Half Title 2
Title Page 4
Copyright Page 5
About the Editors 6
Table of Contents 10
Contributors 12
Abbreviations 14
Preface 16
1. Descriptive Statistics: Principles and Applications 18
2. Random Variables and Their Properties 42
3. Discrete Distributions 68
4. Continuous Distributions 124
5. Family of Weibull Distributions 168
6. Life Distributions 206
7. Dynamics of Data Analysis and Visualization with Python 226
Index 260
Distribution,Theory;,Statistics
Distribution Theory,Statistics

nexusstc/Distribution Theory: Principles and Applications/bac414c3337a49423d1ba5f5946a75c8.pdf

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Apple Academic Press, Incorporated

Apple Academic Press ; CRC Press

CRC Press (Unlimited), Palm Bay, FL, 2024

Canada - English Language, Canada

producers:
Adobe PDF Library 15.0

{"isbns":["1774912147","9781774912140"],"last_page":265,"publisher":"CRC Press/Apple Academic Press"}

"This book aims to provide a thorough understanding of distribution theory and data analysis using statistical software to solve problems related to basic statistics, probability models, and simulation. The volume provides a detailed concept of different distributions used in statistics with their application in real-life situations. Covering the analytical aspects using the latest software, the volume discusses stochastic methods and other statistical methods. It provides statistical data analysis by taking multiple actual situations using the open-source software R version 4.0 and Python 3.0+. A detailed study of the statistical models is provided with examples related to health, agriculture, insurance, and other sectors. Each chapter will help you to increase your knowledge starting from basic statistics to advanced statistics. Key features: Discusses the importance of probability in the field of applied statistics and its importance in day-to-day life; Discusses methods for graphical representations and summary statistics with the help of numerous examples related to actual situations; Considers which distribution theories should be applied in different situations; Shows how to handle real-life problems related to probability; Introduces different ways of data handling using various software; Topics include random variables, statistical properties and theorems, discrete probability models, Weibull distributions, sample generation, Pareto and Burr distributions, data analysis through the freely available statistical package Python, and more. Written clearly for both students and researchers, this volume will be a valuable resource on distribution theories and their applications."-- Provided by publisher

2023-07-05