STA 3000
Statistical Computing · 3 credits · Spring 2027
Requirements
Prereq: {STA 2000 and [(ZICK/ZKTP stdnt grp) or (WEIS/ZKWP stdnt grp and STA-BA) or (NBSTAT-MIN)]} OR {(ENV/BIO/PSY 2100 or STA 2000) & ZKDS stdnt grp}
About this course
Computational statistics is a fundamental part of modern data analysis. This course provides an understanding of the principles and concepts of using modern statistical programing languages for data analysis. Students will learn a programming language, such as R, to handle the manipulation of large data sets, as well as to simulate data, and to import and export data. As an introductory course in statistically oriented programming, no extensive programming background is assumed. Students will gain experience in analyzing both quantitative and qualitative data. They will learn important ideas of programming data structures, functions, iteration, input and output, debugging, logical design, and abstraction. They will learn how to fit basic statistical models and to assess and present the results. Students will also learn how to comment and organize code.
Seat status as of Oct 3, 4:49 AM ET. Seats can change between refreshes.
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