Statistical Experiment Design and Interpretation: An Introduction with Agricultural Examples - Hardcover

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Claire A. Collins and Frances M. Seeney are the authors of Statistical Experiment Design and Interpretation: An Introduction with Agricultural Examples, published by Wiley.

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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.

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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.