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Statistical Experiment Design and Interpretation

Autor Claire A Collins, Frances M Seeney
en Limba Engleză Hardback – sep 1999
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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Specificații

ISBN-13: 9780471960065
ISBN-10: 0471960063
Pagini: 288
Dimensiuni: 175 x 250 x 20 mm
Greutate: 0.69 kg
Ediția:New.
Editura: Wiley
Locul publicării:Chichester, United Kingdom

Public țintă

Agricultural Scientists, Researchers, Agronomists, Agricultural Research Workers involved in designing experiments and analysing data who need a practical working knowledge of Statistics, Advanced Agricultural Students.

Notă biografică

Dr. Liam Collins is the executive director of the Madison Policy Forum, a senior fellow with New America, and a permanent member with the Council on Foreign Relations. Colonel (retired) Collins served in the US Army for 27 years. As a career Special Forces officer, he conducted multiple operational and combat deployments to Afghanistan, Iraq, Bosnia, South America, and the Horn of Africa. In Iraq, Liam conducted operations in Baghdad, Fallujah, Ramadi, and many other cities. Liam retired from the military in 2019 as the founding director of the Modern War Institute and the director of the Department of Military Instruction at the United States Military Academy at West Point. He holds a Bachelor of Science degree in Mechanical Engineering (Aerospace) from the United States Military Academy, and a Master's in Public Affairs and a PhD from Princeton University's School of Public and International Affairs.

Cuprins

Acknowledgements
INTRODUCTION
Notation
A little history
Population versus samples
PLANNING
Formulating the idea
Defining objectives
Defining the population
Formulating hypotheses
Hypothesis testing
Anticipating treatment differences
DESIGN
Variables
Choosing the treatments
Constraints
Replication
Blocking
Randomization
Covariants
Confounding
TRIAL STRUCTURE
Considerations
Single-treatment factor designs
Multi-treatment factor designs
Some other designs
DATA ENTRY AND EXPLORATION
Data entry
Data
Data checking
Data exploration
ANALYTICAL TECHNIQUES
Parametric techniques
Non-parametric techniques
Comparison of parametric and non-parametric techniques
OTHER STATISTICAL TECHNIQUES
Multivariate analysis
Time series analysis
ASPECTS OF COMPUTING
APPENDICES
Glossary of Statistical Terms
Analysis of Variance Formulae
INDEX

Descriere

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 a reala data.