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

Providing practical training supported by a sound theoretical basis, this textbook introduces students to the principals 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 the reader to correctly design their own experiments and identify the most appropriate technique for analysis. The subjects covered include sampling and determining sample reliability, hypothesis testing, relationships between variables, the role and use of computer packages such as: Microsoft Excel, Toolpak and GenStat, and more complex experimental designs such as randomized blocks and split plots. It is suitable for upper-level undergraduate and graduate students of agriculture, horticulture and related disciplines

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

The correct design, analysis and interpretation of plant science experiments is imperative for continued improvements in agricultural production worldwide. The enormous number of design and analysis options available for correctly implementing, analysing and interpreting research can be overwhelming. SAS® is the most widely used statistical software in the world and SAS® OnDemand for Academics is now freely available for academic institutions. This is a user-friendly guide to statistics using SAS® OnDemand for Academics, ideal for facilitating the design and analysis of plant science experiments. It presents the most frequently used statistical methods in an easy-to-follow and non-intimidating fashion, and teaches the appropriate use of SAS® within the context of plant science research.

Logic, research, and experiment; Some basic concepts; The analysis of variance and t tests; The completely randomized design; The randomized complete block design; Mean separation; The latin square design; The split-plot design; The split-split plot; The split-block; Subplots as repeated observations; Transformations; Linear correlation and regression; Curvilinear relations; Shortcur regression methods for equally spaced observations or treatments; Correlalion and regression for more than two variables; Analysis of counts; Heterogeneity; Summary; Improving precision; Selected references; Appendix tables.

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

The experiment in context; Simple experiments and how they can be improved; The general case of block designs; Some useful design concepts; Classes of design; Other blocking systems; The spoilt experiment; Interactions and the confounding of interactions; Some special topics; The people involved.