Data Analytics

College of Arts and Sciences, Interdisciplinary Program

Director: Kim (ECON); Advisory committee: Curran (CISC), Donato (CHEM), High-Pippert (POLS), Knudson (MATH), Marrinan (CISC), Vician (ACCT) 

Program website: https://www.stthomas.edu/data-analytics/

Contact: dataanalytics@stthomas.edu

Data Analytics is the practice of using data to drive strategy and decision-making. Data analysts use cutting-edge statistical and technological tools to discover trends and predict outcomes in nearly every sphere of contemporary life, including healthcare, social media, education, public policy, business, politics, climate change, criminal justice, insurance, travel, and recreation.

The defining characteristic of the interdisciplinary Data Analytics major is the explicit emphasis that statistical, computational, and context-specific knowledge jointly contribute to effective data analysis. Hence, the purpose of the Data Analytics major is three-fold:

  1. To equip students with the statistical and computational tools to conduct meaningful data analyses;
  2. To provide students with the disciplinary-specific context to articulate and comprehend the meaningful data analytic questions within a domain;
  3. To encourage students to develop their skills to effectively communicate data-driven insights.

Major in Data Analytics (B.S.)

Core Requirements*:

The major core  requirements in computer science and statistics equip students with the analytical methods and techniques required to formulate and conduct meaningful data analyses.

  • CISC 131 Introduction to Programming and Problem Solving (4 credits)

Choose one of the following:

    • CISC 260^ Data Fundamentals and Applications (4 credits)
    • CISC 450 Database I (4 credits)
  • CISC 360 Data Visualization (4 credits)
  • STAT 220 Statistics I (4 credits)

Choose one of the following:

    • STAT 320 Statistics II (4 credits)
    • STAT 333 Applied Statisticals Methods (4 credits)
    • ECON 315 Introduction to Econometrics (4 credits)
  • STAT 360 Advanced Statistical Software (4 credits)
  • STAT 400 Data Mining and Machine Learning (4 credits)

*Note: A grade of C- or above must be earned by majors in these courses. 
^Note: Students who receive credit for CISC 260 may not receive credit for CISC 200, CISC 110 or CISC 216.

Note: Students in most domains are strongly encouraged to take STAT 220 with the R lab and should consult with their advisors to determine which STAT 220 lab is appropriate.

Allied Requirements:

Choose one of the following: 

    • MATH 108 Calculus with Review I (4 credits)
      and MATH 109 Calculus with Review II (4 credits)
    • MATH 113 Calculus I (4 credits) 
  • COJO 100 Public Speaking (4 credits) 
  • ENGL 256 Introduction to Professional Writing (4 credits) 

Domain Requirements:

A domain is an area of application for data analytics; its purpose is to provide students the disciplinary-specific context to articulate and understand meaningful questions within a domain that can be addressed using data analytics.  Therefore, each student must select a domain to develop a theoretical foundation to engage their statistical and technological competencies. 

A domain will typically consist of 16–20 credits; the exact number of required credits depends on the domain.  Each domain consists of the relevant introductory and upper-level courses for building a domain-oriented lens for data analysis.  In addition, each domain must provide their students an opportunity for applied data analysis within the context of the domain.  Furthermore, students are required to present their analysis in some formal manner (i.e., visual, written, and/or oral).  Domain departments are responsible for the implementation and approval of any domain-related requirements. 

The suitability and availability of domain courses that support the major potentially varies—both across domains and over time.  Therefore, domain courses must be chosen in consultation with, and approved by, the student’s domain advisor or the domain department chair to ensure the selection of the most appropriate courses. 

Domain courses marked with * may have formal pre-requisites or co-requisites that may be waived on a case-by-case basis in consultation with the student’s domain department chair.

Social Sciences

American Politics [16-20 credits]
  • Introductory courses:
    • POLS 104 Government and Politics (4 credits)
    • POLS 205 Citizen Participation and Public Policy (4 credits)
  • Upper-level courses—choose two of the following:
    • POLS 301 Political Identity and Participation (4 credits)
    • POLS 305 Congress and the Presidency (4 credits)
    • POLS 312 Judicial Process and Politics (4 credits)
  • Applied data analysis—choose one of the following:
    • POLS 404 Seminar in American Politics (4 credits)
    • POLS 495 Individual Study (4 credits)
    • Other approved undergraduate research opportunity (e.g., Young Scholars)
Criminal Justice [20 credits]
  • Introductory courses:
    • SOCI 100 Introduction to Sociology (4 credits)
    • SOCI 200 Introduction to Criminal Justice (4 credits)
  • Upper-level courses:
    • SOCI 210 Research Methods in Sociology (4 credits)
    • SOCI 312 Crime and Delinquency (4 credits)
  • Applied data analysis—choose one of the following:
    • SOCI 495 Individual Study (4 credits)
    • Other approved undergraduate research opportunity (e.g., Young Scholars) and one SOCI 300-level course (4 credits)
Economics [20 credits]
  • Introductory courses:
    • ECON 251 Principles of Macroeconomics (4 credits)
    • ECON 252 Principles of Microeconomics (4 credits)
  • Upper-level courses:

Choose one of the following:

    • ECON 351 Macroeconomic Theory (4 credits)
    • ECON 352 Microeconomic Theory (4 credits)
    • One ECON 300- or 400-level field course (i.e., not ECON 311, ECON 315,ECON 351, or ECON 352)
  • Applied data analysis:

Choose one of the following:

    • ECON 311 Forecasting (4 credits)
    • ECON 315 Introduction to Econometrics (4 credits)
      Note: ECON 315 may not satisfy both the domain requirement and the STAT 320/STAT 333 requirement.
    • Presentation of an approved applied data analysis project (from ECON 311,ECON 315, or other approved undergraduate research opportunity) at an approved internal or external venue.
Geographic Information Systems [16 credits]
  • Introductory course:
    • GEOG 321 Geographic Information Systems (4 credits)
  • Upper-level courses:
    • GEOG 331 Conservation Geography (4 credits)
    • GEOG 350 Geography of Global Health (4 credits)
  • Applied data analysis:
    • GEOG 421 Applied Geographic Information Systems (4 credits)

Natural Sciences

Biology [16 credits]
  • Introductory course—choose one of the following, or consult with Biology Department Chair or Biology Domain Advisor for additional options:
    • BIOL 101 General Biology (4 credits)
    • BIOL 102 Conservation Biology (4 credits)
    • BIOL 105 Human Biology (4 credits)
    • BIOL 110 Genetics and Society
    • BIOL 162 Medical Geology (4 credits)
    • *BIOL 207 Genetics, Ecology Evolution (4 credits)
    • *BIOL 208 Biological Communication and Energetics (4 credits)
    • *BIOL 209 Biology of Sustainability (4 credits)
  • Upper-level courses—to be determined in consultation with Biology Department Chair or Biology Domain Advisor:
    • One BIOL 200-  or 300-level course (4 credits)
    • One BIOL 300-level course (4 credits). Likely course options include:
      • *BIOL 391 Research (4 credits)
      • *BIOL 398 Darwin’s Algorithms (4 credits)
      • *ESCI 310 Environmental Problem Solving (4 credits)
  • Applied data analysis:
    • One BIOL 400-level course (4 credits) that fulfills the “applied data analysis” requirement to be determined in consultation with Biology Department Chair or Biology Domain Advisor. Likely course options include:
      • *BIOL 464 Bioinformatics (4 credits)
      • *BIOL 467 Emerging Infectious Disease (4 credits)
      • *BIOL 480 Urban Ecosystem Ecology (4 credits)
      • *BIOL 486 Seminar (4 credits)
      • *BIOL 491 Research (4 credits)
      • In the absence of an appropriate BIOL 400-level offering, and with the permission of the Biology Department Chair or Biology Domain Advisor, students can pursue OPMT 470 Applied Analytics & Data Visualization (4 credits) to fulfill the “applied data analysis” requirement.
  • Note: Courses marked with * may have pre-requisites or co-requisites. These requirements can be waived in some cases. Students should consult Biology Department Chair or Course Instructor for waiver options.
Chemistry [16-20 credits]
  • Students complete one of the following introductory course options and choose sufficient upper-level courses that focus on a sub-discipline (analytical, organic, physical, or biochemistry) to yield a total of 16 credits of introductory and upper-level courses.
  • Introductory courses—choose one of the following options:
    • CHEM 111 General Chemistry I (4 credits) and CHEM 112 General ChemistryII (4 credits)
    • CHEM 115 Accelerated General Chemistry (4 credits)
    • CHEM 109 General Chemistry for Engineering (4 credits)
      Note: The introductory course requirement may be waived for students with sufficient chemistry background, in which case additional upper-level courseswill be required to reach 16 credits.
  • Upper-level courses—select from the following:
    • *CHEM 201 Organic Chemistry II (4 credits)
    • *CHEM 202 Organic Chemistry II (4 credits)
    • *CHEM 300 Quantitative Analysis (4 credits)
    • *CHEM 320 Instrumental Analysis (4 credits)
    • *CHEM 331 Chemical Thermodynamics and Reaction Dynamics (4 credits)
    • *CHEM 440 Biochemistry I (4 credits)
    • *Other approved CHEM courses at the 200-level or above
  • Applied data analysis—choose one of the following:
    • CHEM 491 Individual Research (2 credits) and CHEM 492 Individual Research(2 credits)
    • Other approved CHEM course that applies data analytics in chemistry
      Note: The applied data analysis credit requirement may be waived for students conducting paid research through Young Scholars grant or similar paid research experience.
Environmental Science[16 credits]
  • Introductory courses − choose one course each from two of the following categories:
    • Biology 
      • BIOL 101 General Biology (4 credits)
      • BIOL 102 Conservation Biology (4 credits)
      • BIOL 105 Human Biology (4 credits)
      • BIOL 162 Medical Geology (4 credits)
      • BIOL 207 Genetics, Ecology Evolution (4 credits)
      • BIOL 209 Biology of Sustainability (4 credits)
    • Chemistry 
      • CHEM 100 Chemistry in Our World (4 credits)
      • CHEM 101 Environmental Chemistry (4 credits)
      • CHEM 109 General Chemistry for ENGR (4 credits)
      • CHEM 111 General Chemistry I (4 credits)
      • CHEM 115 Accelerated General Chemistry (4 credits)
    • Geology
      • GEOL 111 Introductory Physical Geology (4 credits)
      • GEOL 114 The Science of Natural Disasters (4 credits)
      • GEOL 115 Environmental Geology (4 credits)
      • GEOL 162 The Earth’s Record of Climate (4 credits)
  • Upper-level course—choose one of the following:
    • ESCI 310 Environmental Problem Solving (4 credits)
    • ESCI 389 Research (4 credits)
  • Applied data analysis:
    • One ESCI 400-level course (4 credits) that fulfills the “applied data analysis”requirement selected in consultation with ESCI Program Director or ESCI Domain Advisor. Likely options include:
      • ESCI 430 Senior Research Seminar (4 credits)
      • ESCI 491 Research (4 credits)
      • In the absence of appropriate ESCI 400-level offering, and with the permission of the ESCI Program Director or ESCI Domain Advisor,students can pursue OPMT 470 Applied Analytics & Data Visualization(4 credits) to fulfill the “applied data analysis” requirement.
  • NOTE: Because suitability of ESCI 310 and ESCI 430 for Data Analytics major will vary(course projects may or may not lend themselves to data analytics) students should consult ESCI Program Director or ESCI Domain Advisor to select the most appropriate courses.
Geology[16 credits]
  • Introductory course—choose one of the following:
    • GEOL 111 Introductory Physical Geology (4 credits)
    • GEOL 115 Environmental Geology (4 credits)
    • GEOL 162 The Earth’s Record of Climate (4 credits)
  • Upper-level course—choose one of the following:
    • GEOL 252 Earth Surface Processes and Geomorphology (4 credits)
    • GEOL 260 Regional Geology and Geological Field Methods (4 credits)
  • Applied data analysis:—choose two of the following, at least one at the 400-level:
    • GEOL 252 Earth Surface Processes and Geomorphology (4 credits) [If not taken to satisfy the upper-level course requirement above]
    • GEOL 220 Oceanography (4 credits)
    • GEOL 410 Hydrogeology (4 credits)
    • GEOL 462 Advanced Earth’s Record of Climate (4 credits) [If GEOL 162 not taken for introductory course]
Physics [20 credits]
  • Introductory courses:
    • PHYS 211 Classical Physics I (4 credits)
    • PHYS 212 Classical Physics II (4 credits)
    • MATH 114 Calculus II (4 credits)
  • Upper-level courses—choose one of the following:
    • PHYS 215 Foundations of Modern Physics (4 credits)
    • PHYS 225 Applications of Modern Physics (4 credits)
  • Applied data analysis—choose one of the following:
    • PHYS 323 Methods of Experimental Physics (4 credits)
    • PHYS 325 Methods of Computational Physics (4 credits)
Public Health[16 credits]
  • Introductory courses—choose two of the following courses:
    • PUBH 200 Emerging Infectious Disease and Global Health (4 credits)
    • PUBH 210 One Health: Humans, Animals and the Environment (4 credits)
    • PUBH 220 Introduction to Public Health and Social Justice (4 credits)
    • PUBH 225 Global Health and Development (4 credits)
  • Upper-level course:
    • One PUBH 300-level course (4 credits) to be determined in consultation with Health Sciences Chair or Public Health Domain Advisor.  Likely course options include:
      • PUBH 300 Introduction to Epidemiology (4 credits)
  • Applied data analysis:
    • One 400-level PUBH course (4 credits) to be determined in a consultation with Health Sciences Chair or Public Health Domain Advisor. Likely courseoptions include:
      • PUBH 465 Public Health Research Methods (4 credits)
      • PUBH 470 Experiential Learning in Public Health (4 credits)
      • PUBH 491 Research (4 credits)
      • In the absence of appropriate PUBH 400-level offering, and with the permission of the Health Sciences Chair or Public Health Domain Advisor, students can pursue OPMT 470 Applied Analytics & Data Visualization (4 credits) to fulfill the “applied data analysis”requirement.