Understanding Regression Analysis, Michael Patrick Allen

Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat^(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.

By the time you reach the end of the book (and online material) you will have gained:

• A clear appreciation of the importance of a statistical approach to the design of your experiments,
• A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
• Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
• An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.

The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.