Data Analytics - Bachelor of Arts
For information, contact the Department of Statistics, 262 McVey Data Science Building (DSB), 513-529-7828 or email statistics@miamioh.edu.
Data Analytics combines statistical methods, programming skills and deep knowledge in a field of application to extract meaning from large, unstructured or complex data sets with the goal of informing policy, decisions, or scholarly research. Students select a concentration in one of four areas of application:
- Bioinformatics
- Geospatial Analytics
- Social Data Analytics
- Sport Analytics
Students majoring in the Geospatial Analytics concentration may not co-major in Analytics. Students majoring in the Bioinformatics concentration may not minor in Bioinformatics. Students majoring in the Sport Analytics concentration may not minor in Sport Analytics. Students majoring in the Social Data Analytics concentration may count no more than nine (9) credit hours toward this major and a major in Political Science, Gerontology, or Sociology, and they may count no more than six (6) credit hours toward a minor in Political Science, Gerontology or Sociology.
Program Requirements
(3 prerequisite hours, 30-31 core hours, 18-19 concentration hours; 48-55 total hours)
Prerequisites for this program include:
- College Algebra (MTH 122) or Trigonometry (MTH 124) or Precalculus (MTH 125) or Calculus 1 (AP Calculus or MTH 141 or MTH 151) or an ACT Math score of at least 24 or an SAT Math score of at least 580 or at least 12 on the Miami International Math Placement Test.
| Code | Title | Credit Hours |
|---|---|---|
| Core Courses - required for all concentrations | ||
| STA 301 | Applied Statistics | 3-4 |
| or STA 261 | Statistics | |
| or ISA 225 | Principles of Business Analytics | |
| Select one of the following options: | 3-8 | |
| Option 1 | ||
| Mathematical Foundations of Data Analytics | ||
| Option 2 | ||
| Business Calculus | ||
or MTH 151 | Calculus I | |
and | ||
| Finite Mathematical Models | ||
or MTH 222 | Introduction to Linear Algebra | |
or MTH 231 | Elements of Discrete Mathematics | |
| CSE 174 | Fundamentals of Problem Solving and Programming | 3 |
| CSE 148 | Business Computing | 3 |
| or CSE 243 | Problem Analysis Using Computer Tools | |
| STA 247 | Career Preparation and Emerging Tools in Data Analytics | 3 |
| STA 308 | Scripting and AI for Data Processing | 3 |
| STA 363 | Introduction to Statistical Modeling | 3 |
| or ISA 391 | Applied Regression Analysis in Business | |
| or POL 306 | Applied Research Methods | |
| STA 309 | Building, Managing and Exploring Data Sets in Analytics | 3 |
| ENG/STC 285 | Professional Communication for Data Analytics | 3 |
| Select one of the following: | 3 | |
| Technology, Ethics, and Global Society | ||
| Ethics and Digital Media | ||
| Media Law and Ethics | ||
| Society and the Individual | ||
| Introduction to Ethics | ||
| Science and Culture | ||
| Concentration | 18-19 | |
| Select one of the concentrations shown below. | ||
| Students may not select multiple concentrations. | ||
| Total Credit Hours | 48-55 | |
Concentration in Bioinformatics
| Code | Title | Credit Hours |
|---|---|---|
| BIO/MBI 116 | Biological Concepts: Structure, Function, Cellular, and Molecular Biology | 4 |
| BIO/CSE/MBI 256 | Introduction to Programming for the Life Sciences | 3 |
| BIO/CHM/CSE/MBI 466 | Bioinformatics Computing Skills | 3 |
| BIO/CSE/MBI 485 | Bioinformatics Principles | 3 |
| BIO, MBI or CHM at the 200-level or above (BIO 342, MBI 365 or BIO 444 are recommended). | 6 | |
| Total Credit Hours | 19 | |
Concentration in Geospatial Analytics
| Code | Title | Credit Hours |
|---|---|---|
| Select one of the following: | 3-4 | |
| Global Forces, Local Diversity | ||
| Earth's Physical Environment | ||
| Geographic Perspectives on the Environment | ||
| Geography of Urban Diversity | ||
| Geohazards and the Solid Earth | ||
| Select all of the following: | ||
| GEO 242 | Mapping a Changing World | 3 |
| GEO 441 | Introduction to Geographic Information Systems | 3 |
| GEO 442 | Advanced Geographic Information Systems | 3 |
| GEO 448 | Techniques and Applications of Remote Sensing | 3 |
| Select one of the following: | 3 | |
| Python Programming for Geospatial Applications | ||
| Advanced Systematic Geography | ||
| Total Credit Hours | 18-19 | |
Concentration in Social Data
| Code | Title | Credit Hours |
|---|---|---|
| Select one of the following two emphases: | 9 | |
| Political Science emphasis | ||
| Select one of the following: | ||
| Comparative Politics | ||
| American Political System | ||
| Introduction to American Government & Civics | ||
| Public Administration | ||
| World Politics | ||
| Select two more POL courses at the 300 or 400 level. No course may be counted for both the Political Science emphasis and the Advanced Data Courses requirement in this concentration. | ||
| Gerontology/Sociology emphasis | ||
| Select one of the following: | ||
| Sociology in a Global Context | ||
| Aging in American Society | ||
| Global Aging | ||
| Select two of the following: | ||
| Population | ||
| Research Methods | ||
| Social Forces and Aging | ||
| Medical Sociology | ||
| Social Policy and Programs in Gerontology | ||
| Gerontology Capstone Internship | ||
| Aging & Health | ||
| Advanced Data Courses | ||
| Select three of the following, with at least one at the 400 level: | 9-10 | |
| Data & Decision Making in Aging | ||
| Using Large Datasets in the Social Sciences | ||
| Research on Inequality in Aging & Health | ||
| Social Network Analysis | ||
| Public Opinion Laboratory | ||
| Decision-Making in Public Affairs | ||
| Total Credit Hours | 18-19 | |
Concentration in Sport Analytics
| Code | Title | Credit Hours |
|---|---|---|
| SLM 212 | Introduction to Sport Management | 3 |
| SLM 273 | Sport Communication & Media | 3 |
| SLM 275 | Principles of Sport Analytics | 3 |
| SLM 317 | Data Visualization for Sport Analytics | 3 |
| SLM 418 | Applied Sport Analytics | 3 |
| Select one of the following: | 3 | |
| Psychosocial Aspects of Coaching | ||
| Sport Economics | ||
| Principles of Effective Coaching | ||
| Total Credit Hours | 18 | |