Data Analytics A.B.

With an 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 2120	STATISTICS IN APPLICATION	4 sh
STS 2320	STATISTICAL MODELING	4 sh
STS 3270	STATISTICAL COMPUTING FOR DATA MANAGEMENT	4 sh
STS 3470	STATISTICAL COMPUTING FOR SIMULATION AND THEORY	4 sh
CSC 1100	DATA SCIENCE AND VISUALIZATION	4 sh
MTH 2300	MATHEMATICAL METHODS FOR DATA ANALYTICS	4 sh
STS 3300	STATISTICAL METHODS FOR DATA ANALYTICS	4 sh

Electives

Students should take 2 of the following courses

BUS 2110	MANAGEMENT INFORMATION SYSTEMS	4 sh
CSC 1300	COMPUTER SCIENCE I	4 sh
CSC 3211	DATABASE SYSTEMS	4 sh
ECO 4400	ECONOMIC CONSULTING	4 sh
MEA 3290	APPLIED MEDIA ANALYTICS	4 sh
MGT 3100	FOUNDATIONS OF BUSINESS ANALYTICS	4 sh
MGT 4250	DATA VISUALIZATION AND STORYTELLING	4 sh
MGT 4260	DATA MINING FOR MANAGERIAL DECISION MAKING	4 sh
PST 3010	POLICY ANALYSIS	4 sh

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

•  CSC 3211: Database Systems (pre-req: CSC 1300)
•  CSC 4422: Data Mining and Machine Learning (pre-req: CSC 3211 and either CSC 2300 or instructor permission)
•  ECO 4400: Economic Consulting (pre-req: ECO 3200, ECO 3300 and ECO 3120 or ECO 3100)
•  MGT 3100: Big Data Analysis (pre-req: BUS 2110)
•  PST 3010: Policy Analysis (pre-req: PST 2250)

Capstone Requirement

STS 4980

STATISTICS PRACTICUM

4 sh

Students will be required to complete either STS 4980 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