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Presents readers with a user-friendly, non-technical introductionto statistics and the principles of plant and crop experimentation.Avoiding mathematical jargon, it explains how to plan and design anexperiment, analyse results, interpret computer output and presentfindings. Using specific crop and plant case studies, this guidepresents: * The reasoning behind each statistical method is explained beforegiving relevant, practical examples * Step-by-step calculations with examples linked to three computerpackages (MINITAB, GENSTAT and SAS) * Exercises at the end of many chapters * Advice on presenting results and report writing Written by experienced lecturers, this text will be invaluable toundergraduate and postgraduate students studying plant sciences,including plant and crop physiology, biotechnology, plant pathologyand agronomy, plus ecology and environmental science students andthose wanting a refresher or reference book in statistics.
More than a textbook—it’s also a valuable reference book for researchers and crop science professionals! The Handbook of Statistics for Teaching and Research in Plant and Crop Science presents the fundamental concepts of important statistical methods and experimental designs to the students and researchers who need to apply them to their own specific problems. This comprehensive handbook takes what can be the difficult and confusing topics of statistics and experimental design and explains them in easily understandable terms, making them accessible to nearly every reader. More than a student textbook, it is an essential reference for researchers and professionals in a multitude of fields. Designed as a two-semester statistical textbook, the first section of the Handbook of Statistics for Teaching and Research in Plant and Crop Science focuses on statistical concepts, providing a foundation of useful knowledge on which you can base your own research. The second section concentrates on experimental designs in plant and crop sciences. The material is presented in a way that helps readers with a minimum of mathematical background to understand important theories and concepts. Derivations of formulas are avoided, and mathematical symbols are used only when essential. To illustrate the computational procedures, data is drawn from actual experiments. At the end of each chapter, examples and exercises are given to provide clear insight into real-life problems. A comprehensive appendix of clearly presented statistical tables is included. Part One of Handbook of Statistics for Teaching and Research in Plant and Crop Science focuses on statistical methods, principles, and procedures, exploring: methods of display of statistical information, such as tables, diagrams, graphs, etc. symbols and their use in denoting variables descriptions of types of statistical data methods of computation from raw and graphed data the importance of studying variables and dispersion in research the use of normal probability integral tables and their application to practical problems descriptions of different types of experiments, such as determinate and nondeterminate the significance of expected value in research special techniques in descriptive statistics explanations of population, sample, and statistical inference the significance of null hypothesis in research methods of correlation studies assumptions and principles in regression analysis Part Two concentrates on experimental design, principles and procedures, exploring: basic principles of experimental design the fundamental concepts of linear models and analysis of variance method and layout of Completely Randomized Design (CRD) the advantages and disadvantages of Randomized Complete Block Design (RCBD) methods and procedures for comparison of several treatment means the important features of Latin Square Design factorial experiments split plot design completely confounded design analysis of covariance the Chi Square Test of Significance the transformation of experimental data quality control and so much more! The Handbook of Statistics for Teaching and Research in Plant and Crop Science serves not only as a textbook for instructors and students in experimental design and statistics but also as a reference book on plant and crop sciences for professionals and researchers. The comprehensive text is also useful for professionals in other statistic-heavy fields.
Here in one easy-to-understand volume are the statistical procedures and techniques the agricultural researcher needs to know in order to design, implement, analyze, and interpret the results of most experiments with crops. Designed specifically for the non-statistician, this valuable guide focuses on the practical problems of the field researcher. Throughout, it emphasizes the use of statistics as a tool of research—one that will help pinpoint research problems and select remedial measures. Whenever possible, mathematical formulations and statistical jargon are avoided. Originally published by the International Rice Research Institute, this widely respected guide has been totally updated and much expanded in this Second Edition. It now features new chapters on the analysis of multi-observation data and experiments conducted over time and space. Also included is a chapter on experiments in farmers' fields, a subject of major concern in developing countries where agricultural research is commonly conducted outside experiment stations. Statistical Procedures for Agricultural Research, Second Edition will prove equally useful to students and professional researchers in all agricultural and biological disciplines. A wealth of examples of actual experiments help readers to choose the statistical method best suited for their needs, and enable even the most complicated procedures to be easily understood and directly applied. An International Rice Research Institute Book
All students and researchers in environmental and biological sciences require statistical methods at some stage of their work. Many have a preconception that statistics are difficult and unpleasant and find that the textbooks available are difficult to understand. Practical Statistics for Environmental and Biological Scientists provides a concise, user-friendly, non-technical introduction to statistics. The book covers planning and designing an experiment, how to analyse and present data, and the limitations and assumptions of each statistical method. The text does not refer to a specific computer package but descriptions of how to carry out the tests and interpret the results are based on the approaches used by most of the commonly used packages, e.g. Excel, MINITAB and SPSS. Formulae are kept to a minimum and relevant examples are included throughout the text.
Providing practical training supported by a sound theoretical basis, this textbook introduces students to the principles of investigation by experiment and the role of statistics in analysis. It draws on the author's extensive teaching experience and is illustrated with fully worked, contextualized examples throughout, helping readers to correctly design their own experiments and identify the most appropriate technique for analysis. Subjects include sampling and determining sample reliability, hypothesis testing, relationships between variables, the role and use of computer packages such as Microsoft Excel spreadsheet software and GenStat, and more complex experimental designs, such as randomized blocks and split plots. This book is an essential text for students of agriculture, horticulture and related disciplines
As the public and producers becomes more aware of the environmental and economic benefits of precision farming, there has been increased demand for quality training to accurately evaluate spatial variability within fields. Practical Mathematics in Precision Farming provides hand-on training and examples for certified crop consultants (CCAs), farmers, crop consultants, and students (both undergraduate and graduate) on how to conduct to conduct and analyze on-farm studies, write simple programs, use precision techniques to scout for pests and collect soil samples, develop management zones, determine the cost of production, assess the environmental consequences of precision techniques, understand soil test results, and develop site-specific nutrient and plant population algorithms. Using real agronomic examples, the reader is taught the crucial task of managing products and inputs for application at the right rate, place, and time.
Practical Statistics for Geographers and Earth Scientists provides an introductory guide to the principles and application of statistical analysis in context. This book helps students to gain the level of competence in statistical procedures necessary for independent investigations, field-work and other projects. The aim is to explain statistical techniques using data relating to relevant geographical, geospatial, earth and environmental science examples, employing graphics as well as mathematical notation for maximum clarity. Advice is given on asking the appropriate preliminary research questions to ensure that the correct data is collected for the chosen statistical analysis method. The book offers a practical guide to making the transition from understanding principles of spatial and non-spatial statistical techniques to planning a series analyses and generating results using statistical and spreadsheet computer software. Learning outcomes included in each chapter International focus Explains the underlying mathematical basis of spatial and non-spatial statistics Provides an geographical, geospatial, earth and environmental science context for the use of statistical methods Written in an accessible, user-friendly style Datasets available on accompanying website at www.wiley.com/go/Walford
Better experimental design and statistical analysis make for more robust science. A thorough understanding of modern statistical methods can mean the difference between discovering and missing crucial results and conclusions in your research, and can shape the course of your entire research career. With Applied Statistics, Barry Glaz and Kathleen M. Yeater have worked with a team of expert authors to create a comprehensive text for graduate students and practicing scientists in the agricultural, biological, and environmental sciences. The contributors cover fundamental concepts and methodologies of experimental design and analysis, and also delve into advanced statistical topics, all explored by analyzing real agronomic data with practical and creative approaches using available software tools. IN PRESS! This book is being published according to the “Just Published” model, with more chapters to be published online as they are completed.
Choosing and Using Statistics remains an invaluable guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The book is built around a key to selecting the correct statistical test and then gives clear guidance on how to carry out the test and interpret the output from four commonly used computer packages: SPSS, Minitab, Excel, and (new to this edition) the free program, R. Only the basics of formal statistics are described and the emphasis is on jargon-free English but any unfamiliar words can be looked up in the extensive glossary. This new 3rd edition of Choosing and Using Statistics is a must for all students who use a computer package to apply statistics in practical and project work. Features new to this edition: Now features information on using the popular free program, R Uses a simple key and flow chart to help you choose the right statistical test Aimed at students using statistics for projects and in practical classes Includes an extensive glossary and key to symbols to explain any statistical jargon No previous knowledge of statistics is assumed
Providing students with clear and practical advice on how best to organise experiments and collect data so as to make the subsequent analysis easier and their conclusions more robust, this text assumes no specialist knowledge.