| Description |
1 online resource (xiii, 199 pages) |
| Series |
Cambridge series on statistical and probabilistic mathematics |
|
Cambridge series on statistical and probabilistic mathematics.
|
| Contents |
Topics in linear algebra -- Random vectors -- Gauss-Markov estimation -- Normal theory: estimation -- Normal theory: testing -- Analysis of covariance -- Missing observations |
| Summary |
"This book is about the coordinate-free, or geometric, approach to the theory of linear models, more precisely, Model I ANOVA and linear regression models with nonrandom predictors in a finite-dimensional setting. This approach is more insightful, more elegant, more direct, and simpler than the more common matrix approach to linear regression, analysis of variance, and analysis of covariance models in statistics. The book discusses the intuition behind and optimal properties of various methods of estimating and testing hypotheses about unknown parameters in the models."--Jacket |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Print version record |
| Subject |
Linear models (Statistics)
|
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Analysis of variance.
|
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Regression analysis.
|
|
Analysis of covariance.
|
|
MATHEMATICS -- Probability & Statistics -- General.
|
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Analysis of covariance
|
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Analysis of variance
|
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Linear models (Statistics)
|
|
Regression analysis
|
|
Kovarianzanalyse
|
|
Lineares Modell
|
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Regressionsanalyse
|
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Varianzanalyse
|
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Modelos lineares.
|
| Form |
Electronic book
|
| ISBN |
9780511349867 |
|
0511349866 |
|
9780511546822 |
|
0511546823 |
|
