Data Science Minor

Location(s): Brookings Main Campus

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Student standing in front of monitors showing data.

Program Coordinator/Contact

Kurt Cogswell, 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.

Student Learning Outcomes

In the Data Science Minor, students will:

master basic statistical methods.
master intermediate statistical methods.
conduct statistical analyses in discipline/profession-specific contexts.
interpret and report on statistical analyses in discipline/profession-specific contexts.

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