Statistical Experiment Design and Interpretation: An Introduction with Agricultural Examples

Features

• Cover Type: Hard Cover with 288 pages
• Published by: Wiley
• Edition: 1st Edition August 10, 1999
• Written in: English
• ISBN 10 Number: 0471960063
• ISBN 13 Number: 978-0471960065
• Book Dimensions: 9.8 x 6.8 x 0.8 inches
• Weighs: 1.4 pounds

Product Description
Clearly written and free of statistical jargon, this invaluable guide concentrates on the practicalities of statistical analysis for anyone involved with agricultural research.
Each section starts with the key points, giving a quick reference to the contents and plenty of examples using 'real' data.

Successful experiment design starts with a statement of aims. The authors guide the reader through planning an experiment, including defining objectives, considering treatments, measurements of interest and the time and timing of assessments. Advantages and disadvantages of different experiment designs and the importance of data exploration and graphical presentation are covered, as are data collection, storage, validation and verification. Statistical techniques include the t-test, anlaysis of variance, basic regression analysis and non-parametric techniques. Assumptions inherent to these techniques are clearly identified (bearing in mind the principles and aims) without losing the reader in statistical theory. All of the techniques are illustrated with worked examples and give full interpretation of the results. Formulae are kept to a minimum in the main text, but are given in full in the appendix.

Back Cover Copy
Statistical Experiment Design and Interpretation concentrates on the practicalities of statistical analysis for anyone involved in agricultural research. The presentation has not been cluttered with statistical jargon; there are key points at the start of each section giving a quick reference to the contents and plenty of examples using 'real' data.

Successful experiment design starts with a statement of aims. The authors guide the reader through planning an experiment, including defining objectives, considering the treatments, measurements of interest and the time and timing of assessments. Advantages and disadvantages of different experiment designs and the importance of data exploration and graphical presentation are covered, as are data collection, storage, validation and verification. Statistical techniques include the t-test, analysis of variance, basic regression analysis and non-parametric techniques. Assumptions inherent to these techniques are clearly identified (bearing in mind the principles and aims) without losing the reader in statistical theory. All of the techniques are illustrated with worked examples and give full interpretation of the results. Formulae are kept to a minimum in the main text, but are given in full in the appendix.

Reader Reviews
One of the best experimental design books I've read. More attention ought to be paid to design as good design makes the analysis at the end that much simpler