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Essentials of Statistics In Agricultural Sciences - 9781774634448

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9781774634448
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  • Product Details

    Author:
    Pradeep Mishra, Fozia Homa
    Format:
    Paperback
    Pages:
    542
    Publisher:
    Apple Academic Press,CRC Press (March 31, 2021)
    Language:
    English
    ISBN-13:
    9781774634448
    Weight:
    45.625oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260213053419714-20260213.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $99.00
    As low as:
    $94.05
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Audience:
    College/higher education
    Case Pack:
    1
    Imprint:
    Apple Academic Press
  • Overview

    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).