Data Science and Statistics, Bachelor of Science (B.S.)
Program Objectives
Upon successful completion of this program, the graduate will:
- understand the applications and use of data science and statistics in everyday life;
- be able to apply a wide variety of statistical techniques;
- be able to analyze large, complex data sets;
- use computer packages to perform statistical analyses;
- be well qualified for employment in industry, government, and the actuarial profession; and
- be prepared to pursue graduate work in data science or statistics.
Program Requirements
CIP Code: 27.0501
Major
Only courses completed with a grade of at least a “C” will count toward the major requirements.
| Code | Title | Hours |
|---|---|---|
| University Graduation Requirements | ||
| General Education | 36 | |
| Foundations of Learning | ||
| GSD 101 | Foundations of Learning | 3 |
| Upper division courses (42 hours distributed throughout Major/Supporting/Gen Ed/Free Electives categories) | ||
| Major Requirements | ||
| Core Courses | ||
| MAT 239 | Linear Algebra and Matrices | 3 |
| MAT 244 | Calculus II | 4 |
| STA 270 | Applied Statistics | 4 |
| STA 340 | Applied Regression Analysis | 3 |
| STA 498 | Data Science & Statistics Capstone | 3 |
| Choose from nine hours of the following: | 9 | |
| Sports Analytics | ||
| R and Introductory Data Mining 1 | ||
| Sampling Methods | ||
| Nonparametric Statistics | ||
| Applied Probability | ||
| Mathematical Statistics I 2 | ||
| Mathematical Statistics II 2 | ||
| Quality Control & Reliability | ||
| Statistical Methods Using SAS 1 | ||
| R and Introductory Data Mining 1 | ||
| Experimental Design | ||
| Choose from three hours of CSC, DSC, MAT, STA courses numbered 300 or above 3 | 3 | |
| Major Electives | ||
| Choose from one of the following combinations: 4 | 6 | |
| Data Science: | ||
| Data Structures and Programming and Machine Learning | ||
| Discrete Mathematics: | ||
| Discrete Mathematics and Applied Probability | ||
| Statistics: | ||
| Mathematical Statistics II 2 | ||
| Experimental Design | ||
| Choose two courses from one of the following categories: | 6-8 | |
| Accounting: | ||
| Fundamentals of Financial and Managerial Accounting | ||
or ACC 200 | Survey of Accounting | |
| Accounting Information System Risk and Security | ||
| Agriculture: | ||
| Genetics of Livestock Improvement | ||
| Independent Study in Agriculture:___ | ||
or AGR 509 | Agriculture Research Methods and Interpretation | |
| Anthropology and Sociology: | ||
| Primate Ecology & Sociality | ||
| Social Statistics | ||
| Population and Society | ||
| Research Methods in Sociology | ||
| Biology and Environmental Health Sciences: | ||
| One Health: Global Environmental Public Health and Environmental Disease Detectives: Epidemiology | ||
| Genetics and Bioinformatics: Principles and Applications 2 | ||
| Ecology and Conservation Biology 2 | ||
| Computer Information Systems: | ||
| Data Base Management 2 | ||
| Business Data Mining | ||
or BUS 304 | Essentials of MIS | |
| Computer Science and Informatics: | ||
| Data Structures 2 | ||
| Database Systems 2 | ||
| MS Office & Data Analysis 2 | ||
| Finance: | ||
| Personal Money Management | ||
| Financial Institutions | ||
or FIN 311 | Personal Financial Planning | |
or FIN 324 | Principles of Investments | |
| Global Supply Chain Management: | ||
| Essentials of Supply Chain Mgt | ||
| Supply Chain Planning | ||
or MGT 444 | Strategic Sourcing | |
| Government: | ||
| Research and Writing in Political Science 2 | ||
| Capstone Course in Political Science 2 | ||
| Public Opinion & Voting Behavior | ||
| Geosciences: | ||
| Geoscience Data and Techniques 2 | ||
| Geographic Information Systems | ||
| Advanced GIS | ||
| Remote Sensing | ||
| Advanced Geographic Imagery | ||
| Marketing: | ||
| Principles of Marketing (NB) | ||
| Marketing Research and Analysis | ||
or MKT 457 | Experimental Design for Marketing | |
| Physics: | ||
| Electrical Circuits 2 | ||
| Advanced Physics Laboratory 2 | ||
| Classical Mechanics 2 | ||
| Psychology: | ||
| Scientific Literacy in Psychology 2 | ||
| Sensation and Perception | ||
or PSY 315L | Sensation and Perception Lab | |
| Research Literacy in Psychology | ||
| Tests and Measurements | ||
| Risk Management and Insurance: | ||
| Risk Management | ||
| Personal Risk Management | ||
| Advisor-Approved: | ||
Two advisor-approved courses from a department other than the Department of Mathematics and Statistics | ||
| Supporting Course Requirements | ||
| Choose from one of the following: | 3 | |
| Intro to Game Programming | ||
| Introduction to Programming for Science & Engineering | ||
| Computing Concepts and Programming | ||
| Object- Oriented Programming I | ||
| Introduction to Technical and Professional Writing | ||
or ENG 300S | Intro to Tech/Prof Writing | |
| Calculus I G,5 | ||
| Choose from one of the following: | 0-3 | |
| Beginning Ethics | ||
PHI 130S | ||
| Technology and Values | ||
| Free Electives | ||
| Choose from 31-35 hours of free electives | 31-35 | |
| Total Hours | 120 | |
- 1
Must include at least one of DSC 580 R and Introductory Data Mining or STA 575 Statistical Methods Using SAS or STA 580 R and Introductory Data Mining
- 2
Requires a pre-requisite course
- 3
Excluding: any 349 courses, MAT 303 Mathematical Models and Applications, STA 500 . STA 480 Seminar in ___ will count for only approved topics.
- 4
Courses will not count in both the Core and Major Electives categories.
- 5
Three hours count toward Element 2G
- G
Course also satisfies a General Education element. Hours are included within the 36 hours in General Education.