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.

Recent Advancement in Prodrugs Drugs used as medicines have many limitations like low chemical stability, aqueous solubility, or oral absorption/bioavailability, rapid presystemic metabolism, toxicity, inadequate site specificity, or poor patient acceptance/compliance (unwanted adverse effects, unacceptable taste or odor, irritation or pain). Prodrugs design is an approach to overcome these limitations. Key features Covers recent advancements in development of prodrugs Presents balanced synthesis and applications of prodrug chemistry Discusses broad spectrum of prodrug categories and outlines industrial applications Reviews prodrugs in cancer nanomedicine, its therapy and treatment Elucidates mathematical models to study the kinetics of prodrugs This book covers recent advances in the design of prodrugs. It contains all the significant recent examples of prodrug chemistry developments and will aid academics and researchers seeking to generate new projects in the field.

An understanding of the basics, logic, and theory of statistics is essential for agricultural researchers for dealing with the interpretation of data. This volume presents some of the basic and necessary concepts of statistical tools, specifically as applied to the statistics of agriculture and allied fields. It covers basic statistics, design of experiments, sampling techniques, time series, inference outlines, forecasting models, data handling, and statistical software in an easy-to-understand manner that is aimed at students and researchers with little or no mathematical background. In the agriculture scenario, students and researchers face problems that can be addressed with statistical tools, planning of field experiments, collection of data, analysis, interpretation of the data, etc. In this book, statistical theories are discussed with the help of examples from real-life situations in agriculture and allied fields, followed by worked-out examples. Each chapter is followed by a number of problems and questions that will help readers gain confidence in solving those problems. The volume also provides an analysis of how data is important and introduces the reader to using statistical software such as MS Excel, SAS (Statistical Analysis System), JMP, Minitab, and R (from the R Foundation for Statistical Computing).

An understanding of the basics, logic, and theory of statistics is essential for agricultural researchers for dealing with the interpretation of data. This volume presents some of the basic and necessary concepts of statistical tools, specifically as applied to the statistics of agriculture and allied fields. It covers basic statistics, design of experiments, sampling techniques, time series, inference outlines, forecasting models, data handling, and statistical software in an easy-to-understand manner that is aimed at students and researchers with little or no mathematical background. In the agriculture scenario, students and researchers face problems that can be addressed with statistical tools, planning of field experiments, collection of data, analysis, interpretation of the data, etc. In this book, statistical theories are discussed with the help of examples from real-life situations in agriculture and allied fields, followed by worked-out examples. Each chapter is followed by a number of problems and questions that will help readers gain confidence in solving those problems. The volume also provides an analysis of how data is important and introduces the reader to using statistical software such as MS Excel, SAS (Statistical Analysis System), JMP, Minitab, and R (from the R Foundation for Statistical Computing).