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
Summary Checklist for General Education
Code | Title | Hours |
---|---|---|
Element 1 | ||
A: Written Communication | 3 | |
B: Written Communication | 3 | |
C: Oral Communication | 3 | |
Element 2 | ||
Quantitative Reasoning | 3 | |
Element 3 | ||
A: Arts | 3 | |
B: Humanities | 3 | |
Element 4 | ||
Natural Sciences | 6 | |
Element 5 | ||
A: Historical Science | 3 | |
B: Social Behaviorial Science | 3 | |
Element 6 | ||
Diversity of Perspectives Experiences | 6 | |
Total Hours | 36 |
Students are expected to complete Elements 1 and 2 within their first 60 hours of college credit.
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 | |
Student Success Seminar | ||
SCO 100M | Student Success Seminar in Mathematics and Statistics (waived for transfers with 30+ hrs.) | 1 |
Writing Intensive Course (Hrs. incorporated into Major/Supporting/Gen Ed/Free Electives category) | ||
Upper division courses (42 hours distributed throughout Major/Supporting/Gen Ed/Free Electives categories) | ||
ACCT – Data Science and Statistics majors will fulfill ACCT with the following. (Credit hours are incorporated into Major requirements.) | ||
Statistics Capstone | ||
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 498W | 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 | ||
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 | ||
ENG 300 | Introduction to Technical and Professional Writing | 3 |
or ENG 300S | Intro to Tech/Prof Writing | |
MAT 234 | Calculus I (Element 2) ^{G,5} | 4 |
Choose from one of the following: | 0-3 | |
Beginning Ethics (Element 3B) ^{G} | ||
Beginning Ethics (Element 3B) ^{G} | ||
Technology and Values | ||
Domain Knowledge Component | ||
Choose two courses from one of the following categories: | 6-7 | |
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} | ||
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 | ||
Physics: | ||
Electrical Circuits ^{2} | ||
PHY 406 | ^{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 | ||
Advisor-Approved: | ||
Two advisor-approved courses from a department other than the Department of Mathematics and Statistics | ||
Free Electives | ||
Choose from 32-35 hours of free electives | 32-35 | |
Total Hours | 120-127 |
- ^{ 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 2^{G}
- G
Course also satisfies a General Education element. Hours are included within the 36 hours in General Education.