STAT 1061 - DATA SCIENCE FOUNDATIONS
Minimum Credits: 3
Maximum Credits: 3
This course is a general introduction to the rapidly growing field of data science. The topics covered include descriptive statistics, probability, sampling, hypothesis testing, and ANOVA. Broader topics such as regression analysis, model selection, model diagnostics, etc. will also be discussed if time permits. The course will be very hands-on with students actively carrying out the techniques/procedures to foster the ability to reason with data. As part of this process, students will learn the basics of programming in R, and these skills will be reinforced through weekly labs. In developing the core concepts, students will also be exposed to ancillary topics such as data ethics, simulation, and best practices in programming. No previous coding experience nor background in statistics will be assumed.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: LG/SNC Elective Basis
Click here for class schedule information.
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