000			a
999			_c31912 _d31912
008			230419b xxu||||| |||| 00| 0 eng d
020			_a9780367241889
082			_a519.5 _bMON
100			_aMonahan, John F
245			_aPrimer on linear models
260			_bChapman & Hall _c2008 _aBoca Raton :
300			_axiv, 287 p. ; _bill., _c23 cm
365			_b1995.00 _cINR _d01
490			_aTexts in statistical science
504			_aIncludes bibliographical references and index.
520			_aA Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods. This text enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.
650			_aLinear models
650			_aAggregation, Gauss-Markov model
650			_aANOVA
650			_aBest linear unbiased estimator
650			_a Cell means model
650			_aCochran's theorem
650			_aDistributional theory
650			_aEigenvalues
650			_aEstimability
650			_aFirst-order autoregressive error models
650			_a Graam-Schmid orthonormalization
650			_aHypothesis testing
650			_a Pythagorean theorem
650			_a Multivariate linear model
650			_aNested model, two way
650			_aOrthogonal polynomials
650			_a Regression models
650			_aTwo-sample problem
650			_aUnbiased estimators
650			_a Zero estimator
942			_2ddc _cBK