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Applied Regression Analysis


An introduction to regression analysis and statistical learning with an emphasis on mathematical understanding and its software implementation. Programming uses Python.


The Elements of Statistical Learning, Hastie, Tibshirani and Friedman, Springer, corrected 12th printing, 2017.

Credit Hours: 


  • Linear regression: parameter estimation, confidence ellipsoids and prediction intervals, hypothesis tests.
  • Classification: logistic regression, linear discriminant analysis.
  • Basis expansion: polynomial regression, regression splines.
  • Resampling methods: cross-validation, bootstrap.
  • Shrinkage methods.
  • Model selection: information criteria, forward and backward selection, lasso.
  • Decision trees and random forests - bagging, boosting.

(Talata 2020 )


Even Fall Semesters Only

Events Calendar

Using Math

CTE course transformation grant helps Emily Witt, assistant professor of math, develop active learning with student groups in calculus.  Positive results using modules developed with Justin Lyle and Amanda Wilkens, math graduate students, were attained.  Read more

Math and COVID-19: Sources on how math is being used to track the virus and its spread.  AMS link.

A mathematician-musician's breakthrough melds East, West. Read more.

Researcher's innovative approach to flood mapping support emergency management and water officials. Read more.

Nicole Johnson found a way to express her baton twirling using math. See video.