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Essentials of Statistics In Agricultural Sciences
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Essentials of Statistics In Agricultural Sciences

Book Details

Format Hardback or Cased Book
ISBN-10 1771887524
ISBN-13 9781771887526
Publisher Apple Academic Press Inc.
Imprint Apple Academic Press Inc.
Country of Manufacture CA
Country of Publication GB
Publication Date Jul 25th, 2019
Print length 526 Pages
Weight 1,062 grams
Dimensions 24.10 x 16.20 x 3.20 cms
Product Classification: MathematicsAgricultural science
Ksh 25,000.00
Werezi Extended Catalogue 0 in stock

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This volume covers basic statistics, design of experiments, concepts of sampling techniques, time series, inference outlines, and other topics in an easy-to-understand manner and is aimed at students and researchers with little or no mathematical background.

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).


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