STOR
355 Statistical Methods I
Instructor: Zhengyuan Zhu
Summary:
This course presents regression
analysis and related
techniques, and is recommended for students throughout the natural and
social
sciences who are interested in applying regression analysis in their
research
and/or understanding the statistical concepts underlying the
methodology. The
topics include simple and multiple linear regression, matrix
representation of
the regression model, statistical inferences for regression model,
diagnostics
and remedies for multicollinearity, outlier and influential cases,
polynomial
regression and interaction regression models, model selection, weighted
least
square procedure for unequal error variances, and ANOVA model and test.
Statistical software SAS will be used throughout the course to
demonstrate how
to apply the techniques on real data. The main purposes of this course
is to
let students know how to use regression methods properly in data
analysis and
lay the foundation for more advanced studies in statistics.
Prerequisites: STOR 155 or equivalent. Some
familiarity with matrix
algebra recommended, but not required.
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