Appm_header




Semester: Spring 2020
Classroom: ECCR 105
Time: Tue/Thu 3:30-4:45pm
Instructor: Dr. Vanja Dukic
Instructor office Hours:
Tue/Thu 2:30-3:20pm, ECOT322
Main Website

Course Assistant: Ruyu Tan
CA office Hours (in help room ECCR 244):
Tuesdays 9am-10am,
Wednesdays 9am-10am,
Thusdays 11am-12pm,





Department of Applied Mathematics
University of Colorado-Boulder




























Advanced Statistical Modeling



Software and dataset tips:

R can be obtained and installed from www.r-project.org/. That site has many pointers for using R, and programming in it.

A nicely packaged version of R can also be obtained from www.rstudio.org.

The University has a campus license as well as student license for Stata, which is a very friendly and powerful software. If you don't have experience with any statistical software, I'd recommend starting with Stata.

A variety of statistical exercises and examples in R, SPSS, and Stata can be found at the Academic Technology Services website at UCLA: http://www.ats.ucla.edu/stat/

The list of resources specifically for learning and using R is at: https://stats.idre.ucla.edu/r/

Coursera has a 4-week introductory course on R computing: taught by Prof. Roger Peng from Johns Hopkins University. The sessions are monthly.

There are also numerous R books and tutorials, for example:


R in Action by R. Kabacoff
Quick-R site by the R. Kabacoff, based on the "R in Action" book
Data Analysis and Graphics Using R by J. Maindonald
simpleR, by J.Verzani
R Tutorial by C. Yau

A collection of many datasets, from a variety of books and websites, can be found at: http://www.statsci.org/datasets.html

Datasets from our book, Regression Analysis by Example, can be found at the book's website.

Datasets from An Introduction to Generalized Linear Models can be found at the book's website. In addition, UCLA's website has all of the datasets neatly organized; even though it says "SAS" format, you'll be able to see the text data.