【摘 要】
:
Every statistician needs matrices in some form, both in theoretical and practical challenges. Learning the necessary skills requires time and work, as the m
【机 构】
:
UniversityofHelsinki,Finland
【出 处】
:
The 24th International Workshop on Matrices and Statistics(第
论文部分内容阅读
Every statistician needs matrices in some form, both in theoretical and practical challenges. Learning the necessary skills requires time and work, as the multidimensional concept of matrix is far from trivial for most students entering the university.Quite often students of Statistics face matrices for the first time on an elementary course of linear algebra, because it is typically thought that Mathematics should take the responsibility of teaching those topics to everyone. Unfortunately, as the approach on such courses is often quite mathematical, and the connection to Statistics and its applications more or less hidden, it may be rather difficult to find the required motivation for studying the secrets of matrices. However, a certain kind of enthusiasm for matrices should be kindled on the very first course introducing the subject. Therefore, the future statisticians deserve their own courses that do not forget about the theoretical aspects of matrix theory, but instead of too many mathematical details focus on computational approach with appropriate software to investigate real-world applications. In this talk and the mini-symposium we consider various examples of applications and approaches where matrices play a significant role and wonder how to teach matrices within Statistics.
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