Essentials of Statistics In Agricultural Sciences (e-bog) af -
Homa, Fozia (redaktør)

Essentials of Statistics In Agricultural Sciences e-bog

403,64 DKK (inkl. moms 504,55 DKK)
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, i...
E-bog 403,64 DKK
Forfattere Homa, Fozia (redaktør)
Udgivet 24 juli 2019
Længde 526 sider
Genrer Agriculture, agribusiness and food production industries
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9780429758980
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).