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Aug 31, 2024
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ST 310 - Statistical Computing(3.00 cr.)
Reviews a number of statistics topics as a vehicle for introducing students to statistical computing and programming using SAS and R for graphical and statistical analysis of data. Statistics topics include graphical and numerical descriptive statistics, probability distributions, one and two sample tests and confidence intervals, simple linear regression, and chi-square tests. SAS topics include data management, manipulation, cleaning, macros, and matrix computations. Topics in R include data frames, functions, objects, flow control, input and output, matrix computations, and the use of R packages. Lastly, this course also includes an introduction to the resampling and bootstrap approaches to statistical inference. Required for statistics and data science majors.
Prerequisite: ST 210 or ST 265 or EC 220 , or written permission of the department chair. Sessions Typically Offered: Spring Years Typically Offered: Annually
Interdisciplinary Studies: DS/IDS
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