Essentials Of Statistics In Agricultural Sciences

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.

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).

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).

The Book is an introductory text, presenting some of the basic concepts and techniques of Statistical inference. It has been written primarily to suit the students and research workers in the area of agricultural science. An understanding of the logic and theory of statistics is essential for the students of agriculture who are expected to know the techniques of analysing data and drawing useful conclusions. It has been the intention of the authors to keep the book at a readability level appropriate for students who do not have a mathematical background. This book can serve as comprehensive reference source of statistical techniques helpful to agricultural research workers in the interpretation of data.

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 classic book will meet the needs of food and agricultural industries in both their research and business needs. Learn the fundamentals of applying statistics to the business and research needs in the food and agricultural industries. Statistical Methods for Food and Agriculture is a practical, hands-on resource that explores how statistics, a relatively recent development for science and business, facilitates the decision-making process. The range of techniques and applications explained and demonstrated in each of the four major sections of this volume provides a substantial course of study for those in business, government, and universities dealing with food, agriculture, and economics. Part I provides an introduction to the uses of statistics today, including basic concepts and definitions. Part II examines the statistical needs of the food researcher. The emphasis is on design of planned experiments, the analysis of data generated by planned experiments, and decision making in a research environment. Part III deals with statistical procedures that have a wide range of uses for the researcher and business analyst in both business and research situations. Part IV focuses on those statistical methods that have primarily a business application. This important volume is sufficiently detailed to enable the reader to learn and develop without outside assistance. References lead to more detailed presentations for those desiring additional specialized information, and helpful exercises at the end of each chapter permit the book?s use as a textbook as well.

The range of techniques and applications explained and demonstrated in each section provide a substantial course of study for those in business, government, and universities dealing with food, agriculture, and economics. References lead to more detailed presentations for those desiring additional specialized information.

The third edition of this popular introductory text maintains the character that won worldwide respect for its predecessors but features a number of enhancements that broaden its scope, increase its utility, and bring the treatment thoroughly up to date. It provides complete coverage of the statistical ideas and methods essential to students in agriculture or experimental biology. In addition to covering fundamental methodology, this treatment also includes more advanced topics that the authors believe help develop an appreciation of the breadth of statistical methodology now available. The emphasis is not on mathematical detail, but on ensuring students understand why and when various methods should be used. New in the Third Edition: A chapter on the two simplest yet most important methods of multivariate analysis Increased emphasis on modern computer applications Discussions on a wider range of data types and the graphical display of data Analysis of mixed cropping experiments and on-farm experiments