Data Analytics A.B.

With a A. B. in Data Analytics students will be exposed to methods and issues related to managing and analyzing data. This particular degree is meant to be interdisciplinary in nature with requirements in mathematics, statistics, computer science, media analytics, and a requirement of a supporting additional major or minor. 

Foundations

The following courses are required

STS 2120STATISTICS IN APPLICATION

4 sh

STS 2320STATISTICAL MODELING

4 sh

STS 3270STATISTICAL COMPUTING FOR DATA MANAGEMENT

4 sh

STS 3470STATISTICAL COMPUTING FOR SIMULATION AND THEORY

4 sh

CSC 1100DATA SCIENCE AND VISUALIZATION

4 sh

MTH 2300MATHEMATICAL MEHTODS FOR DATA ANALYTICS

4 sh

STS 3300STATISTICAL METHODS FOR DATA ANALYTICS

4 sh

Electives

Students should take 2 of the following courses

BUS 2110MANAGEMENT INFORMATION SYSTEMS

4 sh

CSC 1300COMPUTER SCIENCE I

4 sh

CSC 3211DATABASE SYSTEMS

4 sh

ECO 4400ECONOMIC CONSULTING

4 sh

MEA 3290APPLIED MEDIA ANALYTICS

4 sh

MGT 3100FOUNDATIONS OF BUSINESS ANALYTICS

4 sh

MGT 4250DATA VISUALIZATION AND STORYTELLING

4 sh

MGT 4260DATA MINING FOR MANAGERIAL DECISION MAKING

4 sh

PST 3010POLICY ANALYSIS

4 sh

Note: Some classes have additional pre-reqs not met by the foundations, these are noted in parentheses below.

  •  CSC 301: Database Systems (pre-req: CSC 130)
  •  CSC 401: Data Mining and Machine Learning (pre-req: CSC 230)
  •  ECO 460: Economic Consulting (pre-req: ECO 311, ECO 347 and ECO 302 or ECO 310)
  •  MGT 310: Big Data Analysis (pre-req: BUS 211)
  •  PST 301: Policy Analysis (pre-req: PST 225)

Capstone Requirement

STS 4980STATISTICS PRACTICUM

4 sh

Students will be required to complete either STS 460 or approved capstone focusing on data analytics from another major or minor.

Additional requirements: Students must complete a full minor or a second major in another discipline. A major  in statistics with a concentration in data analytics or minor in computer science, data science, or statistics does not count toward fulfillment of this requirement.

Program Outcomes

To prepare students to manage and analyze large data sets.

To prepare students to think analytically in real-world applications, supporting their actions with ethical decisions from data.

To prepare students to employ principles of descriptive and predictive analytics to address real-world challenges.

To prepare students to articulate analytical conclusions and recommendations in written, oral, and visual formats.

Total Credit Hours: 40

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