Instructor: Dr. Hasthika Rupasinghe

Class meeting: TR 03:30pm - 04:45pm, WA209B

Office: WA324 or Virtual zoom

Online Office Hours: W 12:00-3:00pm Click here to go to office hours

In-person Office Hours: T, R 1.30-2:00pm in WA324

Course Description:

This course covers elements of data management, descriptive statistics, and inferential statistics. The course also examines the variance-bias tradeoff, linear regression, cross-validation, bootstrapping, subset selection, ridge and lasso regression, and choosing optimal models.

Course Objectives:

  1. Students will use a reproducible research work flow.
  2. Students will improve their technology expertise.
  3. Students will learn to apply statistical learning techniques.

Course Text:

An Introdution to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

Optional References:

Reproducible Research with R and RStudio, Second Edition by Christopher Gandrud

The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, and Jerome Friedman

R Graphics Cookbook by Winston Chang - Available via SafariBooksOnline through the Appalachian State University library.

Course Grading:

Attendance and participation: As we are trying to make this experience as close to a regular class as possible, interactivity is important. Therefore you are required have your video on and actively participate in all the class discussions. Attendance will be taken at the end of each class. Students are expected to attend every class. A detailed description of the ASU attendance policy can be found at the following link, [https://academicaffairs.appstate.edu/resources/syllabi-policy-and-statement-information]

Quizzes: I anticipate giving in class quizzes regularly during the semester. As the final quizzes need to be proctored you are required to have your video camera on during quiz time.

Tests: Two tests will be given. The date of each test will be announced at least one week in advance. As the exams need to be proctored you are required to have your video camera on during the exam time.

University Policies

This course conforms with all Appalachian State University policies with respect to academic integrity, disability services, and class attendance. The details of the policies may be found at http://academicaffairs.appstate.edu/resources/syllabi.

Computers and Software

This course will use the RStudio server (https://mathr.math.appstate.edu/) that has the programs listed below and more installed.

You must have an active internet connection and be registered in the course to access the server. To access the server, point any web browser to https://mathr.math.appstate.edu/. You will need to acknowledge the connection is unsecure and possibly add a security exception to your web browser. Use your Appstate Username and Password to access the server. A screen shot of the RStudio server is shown below.

If you have problems with your Appstate Username or Password visit IT Support Services or call 262-6266.

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