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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.
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."
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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