Essentials Of Agricultural Statistics

The Book Essentials Of Agricultural Statistics Is An Effort By The Author To Present The Essentials Of Statistics For The Use By The Students And Professionals Of Agricultural Sciences Alike. Less Of Mathematics And Clear Understanding Of The Concepts Were The Guiding Principles In Writing This Book. The Book Is Organized Systematically To Take The Reader From Descriptive Statistics To Inferential Statistics. The First Chapter Introduces The Subject Matter. Chapter Two Tells About The Data And Sampling Procedures. The Principles Of Descriptive Statistics Are Dealt In Chapter 3 To 6. Chapter 7 To 11 Deal With Inferential Statistics Explaining The Principles Of Probability, Probability Distributions, Statistical Inferences And Testing Of Hypothesis. Analysis Of Variance And Experimental Designs Are Dealt In Chapter 12 To 16. Chapter17 Deals With Chi Square Test, While Chapter 18 Deals With Correlation And Regression. Principles And Types Of Non-Parametric Tests Are Dealt In Chapter 19. The Principles Of Data Transformation Are Presented In Chapter 20. A Chapter On Introduction To Microsoft Excel (Chapter 20) Has Been Provided Along With Notes On Using Excel On Important Topics All Through The Text Book.

This book, Essentials of Statistics in Agriculture Sciences, is an introductory text presenting some of the basic concepts of statistical tools, specifically as applied to the statistics of agriculture and allied fields. An understanding of the basics, logic, and theory of statistics is very essential for agricultural researchers for dealing with the interpretation of data. 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. In the agriculture scenario, students and researchers face problems 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 basic required to analyze research data of Agricultural field experiments and sample surveys are covered. Each definition is given after a relevant discussion. Any one who has completed school finals can easily follow the topics. Examples & illustrations are furnished at appropriate places for easy understanding At the end of each chapter exercises & appli-cation of computer software are also added.

This book ‘Fundamentals of Agricultural Statistics’ deals with the applied aspect of statistical methodologies in agricultural sciences. It includes the theories and concepts relating to Statistical Methods, Probability, Sampling Techniques, Test of Significance and Design of Experiments which have been presented in a lucid and simple manner through real life examples and numerical illustrations. The book would definitely help the students of agriculture and allied sciences in understanding the concepts of statistical theories and their application in agriculture.

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).