A Modern Approach to Regression withR
Author(s) -
Robert Gould
Publication year - 2010
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v033.b03
Subject(s) - regression , computer science , computational biology , statistics , mathematics , biology
I have taught an undergraduate applied regression course for several years, and found few textbooks that are appropriate for modern students. To reveal my prejudices up front, what I want in an applied regression text are data, graphics, and computation. Data, because an applied regression course should give students an approach for understanding the world as it is revealed through data; the regression model is an end to a means but should not be treated as the end itself. Graphics, because not only are they important to modern regression, but they can help students develop a conceptual understanding of regression models. Computation, because data analysis via graphical and numerical regression is not possible without statistical software. The choice of software not only determines the sort of diagnostics and visualizations available to one’s students, but also influences how students understand regression itself.
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