Providing a wide-ranging introduction to the use of linear models in analyzing data, this text presents a vector space and projections approach to the subject. The topics covered include ANOVA, estimation, hypothesis testing, multiple comparison, regression analysis, and experimental design. Also covered are: testing for lack of fit; models with singular covariance matrices; variance component estimation; best linear prediction; colinearity; and variable selection.
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Providing a wide-ranging introduction to the use of linear models in analyzing data, this text presents a vector space and projections approach to the subject. The topics covered include ANOVA, estimation, hypothesis testing, multiple comparison, regression analysis, and experimental design. Also covered are: testing for lack of fit; models with singular covariance matrices; variance component estimation; best linear prediction; colinearity; and variable selection.
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