Applied Regression Analysis and Experimental Design [Hardcover]

For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems.

Stressing principles while keeping computational and theoretical details at a manageable level, Applied Regression Analysis andExperimental Design features an emphasison vector geometry and least squares to unify and provide an intuitive basis for most topics covered& abundant examples and exercises using real-life data sets clearly illustrating practical of data analysis&essential exposure to MINITAB and GENSTAT computer packages , including computer printouts&and important background material such as vector and matrix properties and the distributional properties of quadratic forms.

Designed to make theory work for students, this clearly written, easy-to-understand work serves as the ideal texts for courses Regression, Experimental Design, and Linear Models in a broad range of disciplines. Moreover, applied statisticians will find the book a useful reference for the general application of the linear model.

Preface
Fitting a Model to Data
Introduction
How to Fit a Line
Residuals
Transformations to Obtain Linearity
Fitting a Model Using Vectors and Matrices
Deviations from Means
An Example- Value of a Postage Stamp Over Time
Problems
Goodness of Fit of the Model
Introduction
Coefficient Estimates for Univariate Regression
Coefficient Estimates for Mulitvariate Regression
ANOVA Tables
The F Test
The Coefficient of Determination
Predicted Values of Y and Confidence Intervals
Residuals
Reduced Models
Pure Error and Lack of Fit
Example- Lactation Curve
Problems
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