Minor

The minor in Data Science & Statistics requires six units. Grade point average of coursework comprising the minor must be no less than 2.00, with no course grade below C- (1.70). Units include:

The Data Science and Statistics Minor

Six classes

  • 1 unit in introductory statistical methods, chosen from:

    • DSST189 Introduction to Statistical Modeling

    • AMST298 Special Topics: Digital Humanities

    • BIOL320 Experimental Design and Biostatistics

    • BUAD202 Statistics for Business and Economics

    • CHEM300 Measurement Statistics

    • CHEM301 Quantitative Methods of Chemical Analysis

    • CMSC327 Machine Learning

    • ECON170 Statistical Analysis for Business and Economics

    • ECON242 Data Analysis & Computing for Economics & Business

    • ECON270 Introductory Econometrics

    • ECON249 Quantitative Social Science

    • DSST329 Probability

    • PLSC270 Social Science Inquiry

    • PSYC200 Methods and Analysis

    • RHCS245 Digital Humanities

    • SOC211 Sociological Research Methods

  • Three core courses:

  • Two additional electives, chosen from, (can not double count with an introductory course):

    • BIOL336 Eco-epidemiology with Lab

    • CHEM300 Quantitative Methods of Chemical Analysis

    • CHEM314 Physical Chemistry Laboratory I

    • CHEM315 Physical Chemistry Laboratory II

    • CMSC325 Database Systems

    • CMSC327 Machine Learning

    • CMSC 336 Music Informatics

    • CMSC395 Special Topics: Introduction to Human Computer Interaction

    • CMSC395 Special Topics: Natural Language Processing

    • ECON242 Data Analysis & Computing for Economics & Business

    • ECON270 Introductory Econometrics

    • ECON370 Advanced Econometrics

    • ECON373 Forecasting & Time-Series Analysis

    • GEOG260 Foundations of Geospatial Analysis

    • GEOG360 Environmental Remote Sensing

    • GEOG365 Advanced Spatial Analysis

    • LING390 Independent Study: Corpus Linguistics (0.5 credits)

    • LING297 Selected Topics: Pragmatics (0.5 credits)

    • MATH395 Special Topics: Computational Modeling in Public Health

    • MATH395 Special Topics: The Study of Cause and Effect

    • PSYC300 Methods and Analyses Core Project

    • PSYC343 Psycholinguistics

    • RHCS412/AMST398 Special Topics: Digital Humanities Workshop

Students may petition to replace an introductory statistical methods course with an additional elective; they may also petition to include other advanced courses as electives with permission of the program coordinator. Normally only one elective should be an independent study or independent research course. The minor may not be combined with the major concentration in Data Science and Statistics (in Math or Computer Science) nor can it be combined with the Business Analytics concentration.

The minor requires three core courses (DSST 289, DSST 389, and RHCS 345). The core courses are required for the minor and are not negotiable. The minor also requires one credit or an introductory course and two credits of elective, for which there is some flexibility, including the ability to take an extra elective in place in the introductory course. Note that the minor is open to all students with the exception that it may not be combined with the business school's concentration in Data Analytics.