Practical statistics and experimental design for plant and crop science.

Chapter 1.- Basic principles of experimentation.
Chapter 2.- Basic statistical calculations.
Chapter 3.- Basic data summary.
Chapter 4.- The normal distribution, the t-distribution confidence intervals.
Chapter 5.- Introduction to hypothesis testing.
Chapter 6.- Comparison of two independent sample means.
Chapter 7.- Linear regression and correlation.
Chapter 8.- Curve fitting.
Chapter 9.- The completely randomised design.
Chapter 10.- The randomised block design.
Chapter 11.- The latin square design.
Chapter 12.- Factorial experiments.
Chapter 13.- Comparison of treatment means.
Chapter 14.- Checking the assumptions and transformation of data.
Chapter 15.- Missing values and incomplete blocks.
Chapter 16.- Split designs.
Chapter 17.- Comparison of regression lines and analysis of covariance.
Chapter 18.- Analysis of counts.
Chapter 19.- Some non-parametric methods.
--Appendix 1.- The normal distribution function
--Appendix 2.- Percentage points of the normal distribution
--Appendix 3.- Percentage points of the t-distribution
--Appendix 4a.- 5 per cent points of the F-distribution.
--Appendix 4b.- 2.5 per cent points of the F-distribution.
--Appendix 4c.- 1 per cent points of the F-distribution.
--Appendix 4d.- 0.1 per cent points of the F-distribution.
--Appendix 5.- Percentage points of the sample correlation coefficient (r) when the population correlation coefficient is 0 and n is the number of X, Y pairs.
--Appendix 6.- 5 percent points of the studentised range, for use in tukey and SNK tests.
--Appendix 7.- Percentage points of the chi-square distribution.
--Appendix 8.- Probabilities of S or fewer successes in the binomial distribution with n trials and p=0.5.
--Appendix 9.- Critical values of T in the wilcoxon signed rank or matched pairs test.
--Appendix 10.- Critical values of U in the Mann-Whitney test.

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.