Statistical Designs And Analysis For Agricultural Field Experiments

This text provides statistical and biometrical procedures for designing, conducting, analyzing and interpreting field experiments. It addresses the most important research topics in agriculture, including agronomy, breeding and pasture trials; farming systems research; and intercropping research.

The book is written in easy to understand language, in short paragraphs and is fully supported by adequate examples. The book consists of 11 chapters.

Understand language, in short paragraphs and is fully supported by adequate examples.

The book consists of 12 chapter. The I is related to terminology in experimental design while the II devoted to completely randomized block design and randomized block design for agricultural experiments in the field. The III is devoted to factorial experiments in randomized block design involving two or more factoThe IV deals with partially confounded and fully confounded factorial experiments. The cheaper V deals with split plot design and strip plot design. The VI deals with repetition of experiments over years with sampling in agricultural trials at cultivator's fields, while VII is related to sustainability of crop sequences and treatments. The VIII deals with analysis of trials at cultivators' fields while the IX deals with sampling techniques. X deals with co-relation and regression studies. The XI spells out the agronomic considerations and synthesis of system based results. The last XII deals with methodology and procedure for farming systems research while the schedule for date collection for farming systems characterization and evaluation is given in appendix.

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.

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.

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.