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ISBN: 3642447597 364210472X 9786613369512 1283369516 3642104738 Year: 2011 Publisher: New York : Springer,
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In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple “tricks” which simplify and clarify the treatment of a problem—both for the student and for the professor. Of course, the concept of a trick is not uniquely defined—by a trick we simply mean here a useful important handy result. In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.
Linear models (Statistics) --- Matrix analytic methods --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Models, Linear (Statistics) --- Statistics. --- Statistical Theory and Methods. --- Mathematical models --- Mathematical statistics --- Statistics --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics
Book
ISBN: 3642329306 3642329314 Year: 2013 Publisher: New York : Springer,
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This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook. It is intended for students and researchers who need quick access to useful formulas appearing in the linear regression model and related matrix theory. This is not a regular textbook - this is supporting material for courses given in linear statistical models. Such courses are extremely common at universities with quantitative statistical analysis programs.
Linear regression. --- Mathematics. --- Matrix theory. --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Linear systems --- Mathematical models. --- Formulae. --- Formulas (Mathematics) --- Mathematical formulae --- Mathematical formulas --- Systems, Linear --- Statistics. --- Algebra. --- Econometrics. --- Statistical Theory and Methods. --- Linear and Multilinear Algebras, Matrix Theory. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Differential equations, Linear --- System theory --- Mathematical statistics. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Economics, Mathematical --- Statistics --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Statistics . --- Mathematical analysis
Digital
ISBN: 9783642104732 Year: 2011 Publisher: Berlin, Heidelberg Springer Berlin Heidelberg
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Digital
ISBN: 9783642329319 Year: 2013 Publisher: Berlin, Heidelberg Springer
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This is an unusual book because it contains a great deal of formulas. Hence it is a blend of monograph, textbook, and handbook. It is intended for students and researchers who need quick access to useful formulas appearing in the linear regression model and related matrix theory. This is not a regular textbook - this is supporting material for courses given in linear statistical models. Such courses are extremely common at universities with quantitative statistical analysis programs.
Statistical science --- Quantitative methods (economics) --- Economics --- Algebra --- Mathematical statistics --- Business economics --- algebra --- matrices --- economie --- statistiek --- econometrie --- wiskunde --- statistisch onderzoek
Book
ISBN: 9783642104732 9783642104725 Year: 2011 Publisher: Berlin, Heidelberg Springer Berlin Heidelberg
Abstract | Keywords | Export | Availability | Bookmark
Loading...Choose an application
- Reference Manager
- EndNote
- RefWorks (Direct export to RefWorks)
In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple tricks which simplify and clarify the treatment of a problem both for the student and for the professor. Of course, the concept of a trick is not uniquely defined by a trick we simply mean here a useful important handy result. In this book we collect together our Top Twenty favourite matrix tricks for linear statistical models.
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