Theory and Application of Regression and Analysis of Variance-I |
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Description The aim of this course is to
provide an introduction to theory and application of regression and
analysis of variance. In particular, we will cover estimation and testing theory for least squares fits under general, Gauss-Markov, and related assumptions; diagnostic tools; prediction and model selection in linear regression; and generalized linear models. The lectures will mainly focus on the theory and provide examples of applications. The homework assignments will provide the opportunity to implement many of the methods on real data. See the syllabus for more information. Prerequisites Linear algebra, Introductory
Statistics and Probability.
Reading listAll of the four books below are
on reserve at Wendt library.
ComputingAs our main text book, we will use
We will use R, a freely available
implementation of S language, as our computing environment.
Discussion sessions will include basic information on related R functions. Tutorials are available on the R website. Grading
*Percentages might be subject to change. |
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