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Preface.<br /> <br /> Basic Principles of Experimentation.<br /> <br /> Basic Statistical Calculations.<br /> <br /> Basic Data Summary.<br /> <br /> The Normal Distribution, the t-Distribution and Confidence Intervals.<br /> <br /> Introduction to Hypothesis Testing.<br /> <br /> Comparison of Two Independent Sample Means.<br /> <br /> Linear Regression and Correlation.<br /> <br /> Curve Fitting.<br /> <br /> The Completely Randomised Design.<br /> <br /> The Randomised Block Design.<br /> <br /> The Latin Square Design.<br /> <br /> Factorial Experiments.<br /> <br /> Comparison of Treatment Means.<br /> <br /> Checking the Assumptions and Transformation of Data.<br /> <br /> Missing Values and Incomplete Blocks.<br /> <br /> Split Plot Designs<br /> <br /> Comparison of Regression Lines and Analysis of Covariance.<br /> <br /> Analysis of Counts.<br /> <br /> Some Non-parametric Methods.<br /> <br /> Appendix 1: The Normal Distribution Function.<br /> <br /> Appendix 2: Percentage Points of the Normal Distribution.<br /> <br /> Appendix 3: Percentage Points of the t-Distribution.<br /> <br /> Appendix 4a: 5 Per Cent Points of the F-Distribution.<br /> <br /> Appendix 4b: 2.5 Per Cent Points of the F-Distribution.<br /> <br /> Appendix 4c: 1 Per Cent Points of the F-Distribution.<br /> <br /> Appendix 4d: 0.1 Per Cent Points of the F-Distribution.<br /> <br /> 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.<br /> <br /> Appendix 6: 5 Per Cent Points of the Studentised Range, for Use in Tukey and SNK Tests.<br /> <br /> Appendix 7: Percentage Points of the Chi-Square Distribution.<br /> <br /> Appendix 8: Probabilities of S or Fewer Successes in the Binomial Distribution with n 'trials' and p = 0.5.<br /> <br /> Appendix 9: Critical Values of T in the Wilcoxon Signed Rank or Matched Pairs Test.<br /> <br /> Appendix 10: Critical Values of U in the Mann-Whitney Test.<br /> <br /> References.<br /> <br /> Further Reading.<br /> <br /> Index.

"...suitable for a practical course to science students wishing to appreciate statistical methods in agricultural and environmental research." (Short Book Reviews, Vol. 21, No. 2, August 2001)<br /> <br /> "...useful to undergraduate students..." (Zentralblatt MATH, Vol. 961, 2001/11)

Alan G. Clewer and David H. Scarisbrick<br /> T. H. Huxley School of Environment, Earth Sciences and Engineering, Imperial College at Wye, Ashford, Kent, UK

Practical Statistics and Experimental Design for Plant and Crop Science provides an introduction to the principles of plant and crop experimentation. Avoiding mathematical jargon, this text explains how to plan and design an experiment, analyse results, interpret computer output and present findings. Using specific crop and plant case studies this user-friendly guide presents: <ul> <li>The reasoning behind each statistical mathod before giving practical examples</li> <li>Step-by-step calculations with examples linked to three computer packages (MINITAB, GENSTAT and SAS)</li> <li>Exercises at the end of many chapters</li> <li>Advice on presenting results and report writing</li> </ul> Written by experienced lecturers, this text will be invaluable to undergradaute and postgraduate students studying plant sciences, including plant and crop physiology, biotechnology, plant pathology and agronomy, plus ecology and environmental science students and those wanting a refresher or reference book in statistics.

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