Statistical Methods in Agriculture and Experimental Biology includes all the basic statistical methods relevant to their work. Undergraduate and postgraduate majors in those subjects will find its information most essential to their studies.Material on more advanced topics- not usually discussed in an introductory text-focuses on multiple regression, incomplete block experimental design, confounded and split-plot experimental designs, non-linear and log-linear models, and repeated measurements. The authors believe that research scientists should be aware of the potential benefits of those more advanced methods in their work.Particular emphasis is placed upon the assumptions implicit in statistical methods: a full chapter is devoted to that important aspect. It also stresses the importance of designing experiments properly, particularly in using small, natural blocks and factorial treatment structure, and of using available resources efficiently, and extracting all information from the data.