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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