Data Science and Statistics, Bachelor of Science (B.S.)
Program Objectives
Upon successful completion of this program, the graduate will:
- be able to apply data science and statistical techniques to real-world problems and interpret the results;
- be able to produce high-quality visualizations; and
- be able to communicate data science and statistical results to a diverse audience.
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 | ||
| Essential Education | 30 | |
| Foundations of Learning | ||
| GSD 101 | Foundations of Learning | 3 |
| Upper division courses (hours are distributed throughout Major/Supporting/Essential Ed/Free Electives categories) | 39 | |
| Major Requirements | ||
| Core Courses | ||
| CSC 174 | Introduction to Programming for Science & Engineering | 3 |
| or CSC 190 | Object-Oriented Programming I | |
| ENG 300 | Introduction to Technical and Professional Writing | 3 |
| 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 |
| DSC 580 | R and Introductory Data Mining | 3 |
| or STA 580 | R and Introductory Data Mining | |
| STA 575 | Statistical Methods Using SAS | 3 |
| Choose from three hours of the following: 3 | 3 | |
| Sports Analytics | ||
| Sampling Methods | ||
| Nonparametric Statistics | ||
| Applied Probability | ||
| Mathematical Statistics I 1 | ||
| Mathematical Statistics II 1 | ||
| Quality Control & Reliability | ||
| 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: | 6 | |
| Data Science: | ||
| Data Structures and Programming | ||
| Machine Learning | ||
| Discrete Mathematics: | ||
| Discrete Mathematics | ||
| Applied Probability | ||
| Statistics (recommended for students who want to attend graduate school): | ||
| Mathematical Statistics II 1 | ||
| 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 1 | ||
| Ecology and Conservation Biology 1 | ||
| Management Information Systems: | ||
| Database Management | ||
| Business Data Mining | ||
or BUS 304 | Essentials of MIS | |
| Computer Science and Informatics: | ||
| Data Structures 1 | ||
| Database Systems 1 | ||
| MS Office & Data Analysis 1 | ||
| 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 Management | ||
| Supply Chain Planning | ||
or MGT 444 | Strategic Sourcing | |
| Government: | ||
| Research and Writing in Political Science 1 | ||
| Capstone Course in Political Science | ||
| Public Opinion & Voting Behavior | ||
| Geosciences: | ||
| Geoscience Data and Techniques 1 | ||
| 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 1 | ||
| Advanced Physics Laboratory 1 | ||
| Classical Mechanics 1 | ||
| Psychology: | ||
| Scientific Literacy in Psychology 1 | ||
| Sensation and Perception | ||
| Research Literacy in Psychology | ||
| Tests and Measurements | ||
| Risk Management and Insurance: | ||
| Principles of Risk and Insurance | ||
or RMI 374 | Fundamentals of Life and Health Insurance | |
or RMI 376 | Excess & Surplus Lines | |
or RMI 382 | Claim Handling Principles and Practices | |
| Risk Management | ||
| Advisor-Approved: | ||
Two advisor-approved courses from a department other than the Department of Mathematics and Statistics | ||
| Supporting Course Requirements | ||
| MAT 234 | Calculus I (Element 2A) E,4 | 1 |
| Beginning Ethics (Element 3B) E | ||
| Free Electives | ||
| Choose from 37-39 hours of free electives | 37-39 | |
| Total Hours | 120 | |
- 1
Requires a pre-requisite course
- 2
Excluding: any 349 courses. STA 480 Seminar in ___ will count for only approved topics.
- 3
Courses will not count in different categories.
- 4
Three hours count toward Element 2AG
- E
Course also satisfies an Essential Education element. Hours are included within the 30 hours in Essential Education.
Key:
- E
Course satisfies an Essential Education element.
- *
Course must be taken in semester indicated.
Upper division courses: All students are required to have a minimum of 39 hrs. upper division (300-level or above) courses distributed throughout Major/Supporting/Essential Ed/Free Electives categories.
Data Science and Statistics B.S. - Statistics Combination (Recommended for students who want to attend graduate school)
| First Year | ||
|---|---|---|
| First Semester | Hours | |
| GSD 101 | Foundations of Learning | 3 |
| STA 270 | Applied Statistics | 4 |
| MAT 234 | Calculus I (E-2A (3 hours)) | 4 |
| ENG 101 | Reading, Writing, and Rhetoric | 3 |
| Hours | 14 | |
| Second Semester | ||
| ENG 102 | Research, Writing, and Rhetoric (E-1B) E * | 3 |
| STA 340 | Applied Regression Analysis | 3 |
| CSC 174 or CSC 190 |
Introduction to Programming for Science & Engineering or Object-Oriented Programming I |
3 |
| MAT 244 | Calculus II | 4 |
| E-3A (Arts) E | 3 | |
| Hours | 16 | |
| Second Year | ||
| First Semester | ||
| MAT 239 | Linear Algebra and Matrices | 3 |
| E-1C (Communication) E | 3 | |
| #-2B (Natural Sciences) E | 3 | |
| DSC/STA Elective | 3 | |
| MAT 254 | Calculus III | 4 |
| Hours | 16 | |
| Second Semester | ||
| CSC/DSC/MAT/STA Elective | 3 | |
| Domain Knowledge Course #1 | 3 | |
| PHI 130 | Beginning Ethics (E-3B) E | 3 |
| E-2B (Natural Sciences) E | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Third Year | ||
| First Semester | ||
| STA 575 | Statistical Methods Using SAS | 3 |
| STA 585 | Experimental Design | 3 |
| Domain Knowledge Course #2 Up | 3 | |
| E-4B E | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Second Semester | ||
| ENG 300 | Introduction to Technical and Professional Writing | 3 |
| DSC 580 | R and Introductory Data Mining | 3 |
| E-4B E | 3 | |
| Free Elective Up | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Fourth Year | ||
| First Semester | ||
| STA 498 | Data Science & Statistics Capstone | 3 |
| STA 520 | Mathematical Statistics I | 3 |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Second Semester | ||
| STA 521 | Mathematical Statistics II | 3 |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 2 | |
| Free Elective Up | 3 | |
| Hours | 14 | |
| Total Hours | 120 | |
Data Science and Statistics B.S. - Data Science Combination
| First Year | ||
|---|---|---|
| First Semester | Hours | |
| GSD 101 | Foundations of Learning | 3 |
| STA 270 | Applied Statistics | 4 |
| MAT 234 | Calculus I (E-2A (3 hours)) | 4 |
| ENG 101 | Reading, Writing, and Rhetoric | 3 |
| Hours | 14 | |
| Second Semester | ||
| ENG 102 | Research, Writing, and Rhetoric (E-1B) E * | 3 |
| STA 340 | Applied Regression Analysis | 3 |
| CSC 174 or CSC 190 |
Introduction to Programming for Science & Engineering or Object-Oriented Programming I |
3 |
| MAT 244 | Calculus II | 4 |
| E-3A (Arts) E | 3 | |
| Hours | 16 | |
| Second Year | ||
| First Semester | ||
| MAT 239 | Linear Algebra and Matrices | 3 |
| E-1C (Communication) G | 3 | |
| #-2B (Natural Sciences) G | 3 | |
| DSC/STA Elective | 3 | |
| CSC 189 or CSC 190 |
Computing Concepts and Programming or Object-Oriented Programming I |
3 |
| Hours | 15 | |
| Second Semester | ||
| CSC/DSC/MAT/STA Elective | 3 | |
| Domain Knowledge Course #1 | 3 | |
| PHI 130 | Beginning Ethics (E-3B) E | 3 |
| E-2B (Natural Sciences) E | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Third Year | ||
| First Semester | ||
| STA 575 | Statistical Methods Using SAS | 3 |
| Domain Knowledge Course #2 Up | 3 | |
| E-4B E | 3 | |
| Free Elective Up | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Second Semester | ||
| ENG 300 | Introduction to Technical and Professional Writing | 3 |
| DSC 580 | R and Introductory Data Mining | 3 |
| E-4B E | 3 | |
| Free Elective Up | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Fourth Year | ||
| First Semester | ||
| STA 498 | Data Science & Statistics Capstone | 3 |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Second Semester | ||
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective Up | 3 | |
| Major Elective | 3 | |
| Hours | 15 | |
| Total Hours | 120 | |
Data Science and Statistics B.S. - Discrete Math Combination
| First Year | ||
|---|---|---|
| First Semester | Hours | |
| GSD 101 | Foundations of Learning | 3 |
| STA 270 | Applied Statistics | 4 |
| MAT 234 | Calculus I (E-2A (3 hours)) | 4 |
| ENG 101 | Reading, Writing, and Rhetoric | 3 |
| Hours | 14 | |
| Second Semester | ||
| ENG 102 | Research, Writing, and Rhetoric (E-1B) E * | 3 |
| STA 340 | Applied Regression Analysis | 3 |
| CSC 174 or CSC 190 |
Introduction to Programming for Science & Engineering or Object-Oriented Programming I |
3 |
| MAT 244 | Calculus II | 4 |
| E-3A (Arts) E | 3 | |
| Hours | 16 | |
| Second Year | ||
| First Semester | ||
| MAT 239 | Linear Algebra and Matrices | 3 |
| E-1C (Communication) E | 3 | |
| #-2B (Natural Sciences) E | 3 | |
| DSC/STA Elective | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Second Semester | ||
| CSC/DSC/MAT/STA Elective | 3 | |
| Domain Knowledge Course #1 | 3 | |
| PHI 130 | Beginning Ethics (E-3B) E | 3 |
| E-2B (Natural Sciences) E | 3 | |
| Free Elective | 3 | |
| Hours | 15 | |
| Third Year | ||
| First Semester | ||
| STA 575 | Statistical Methods Using SAS | 3 |
| Domain Knowledge Course #2 Up | 3 | |
| E-4B E | 3 | |
| Free Elective Up | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Second Semester | ||
| ENG 300 | Introduction to Technical and Professional Writing | 3 |
| DSC 580 | R and Introductory Data Mining | 3 |
| STA 470 | Applied Probability | 3 |
| E-4B E | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Fourth Year | ||
| First Semester | ||
| STA 498 | Data Science & Statistics Capstone | 3 |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Second Semester | ||
| MAT 306 | Discrete Mathematics | 3 |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective | 3 | |
| Free Elective Up | 3 | |
| Hours | 15 | |
| Total Hours | 120 | |