Data Science Minor

Location(s): Brookings Main Campus

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Student standing in front of monitors showing data.

Program Coordinator/Contact

Eun Heui Kim, Department Head
Donna Flint, Assistant Department Head
Department of Mathematics and Statistics
Chicoine Architecture, Mathematics and Engineering Hall 209
605-688-6196

Program Information

The Data Science minor provides training in the discipline-specific and profession-specific application of data science concepts and methods to students enrolled in a wide variety of programs and majors.

Course Delivery Format

Program courses are delivered on campus, in classroom and laboratory settings, and online.

Academic Requirements

A grade of C or better is required for all courses in the minor.

Requirements for Data Science Minor: 18 Credits

STAT 101 - Introduction to Data Science Credits: 3
STAT 281 - Introduction to Statistics (COM) [SGR #5, HSDC] Credits: 3
or STAT 381 - Introduction to Probability and Statistics (COM) Credits: 3
STAT 442 - Exploratory and Cloud-Based Data Analysis Credits: 3

Electives

Select nine credits from the following. Credits: 9

DSCI / ECON 453 - Risk Management - Personal and Business Credits: 3
ECON 423 - Introduction to Econometrics (COM) Credits: 3
GEOG 382 - Quantitative Research Methods in Geography Credits: 2
GEOG 382L - Quantitative Research Methods in Geography Lab Credits: 1
INFO 101 - Introduction to Informatics Credits: 3
POLS 388 - Research Methods Credits: 3
PSYC 477 - Psychology Testing and Measurement (COM) Credits: 3
SOC 307 - Research Methods I (COM) Credits: 3
SOC 308 - Research Methods II (COM) Credits: 3
STAT 383 - Geospatial Data Analysis Credits: 3
STAT 410 - SAS Programming Credits: 3
STAT 414 - Basic R Programming Credits: 1
STAT 415 - R Programming Credits: 3
STAT 435 - Applied Bioinformatics Credits: 3
STAT 441 - Statistical Methods II Credits: 3
STAT 445 - Nonparametric Statistics (COM) Credits: 3
STAT 451 - Predictive Analytics I Credits: 3
STAT 453 - Applied Bayesian Statistics Credits: 3
STAT 460 - Time Series Analysis (COM) Credits: 3