Analytics Co-Major
For information, contact the Department of Statistics, 311 UPH, 513-529-7828, or the Department of Information Systems and Analytics, 3095 FSB, 513-529-4826.
Analytics describes the extensive use of data to guide evidence-based decision-making. This field has emerged during a time when massively large data sets are being collected throughout society. Analytics lives at the junction between numerous traditional disciplines including information systems and statistics. This program will provide a framework for thinking about the collection and use of so-called "big data" and students will develop skills for handling structured and unstructured data sets and for developing models to predict behavior in data-rich environments.
The term "co-major" is unique and indicates that students must be concurrently enrolled in and must complete another major at Miami University. The co-major complements this primary major, which provides significant depth and breadth in an academic discipline. There is no specific degree designation for the co-major; students receive the degree designation of their primary major. Students may earn either the Business Analytics Minor or the Analytics Co-Major.
Program requirements
Complete a major in one of the divisions of the university.
| Code | Title | Credit Hours |
|---|---|---|
| CORE coursework to be satisfied by all co-majors (18-19 hours) | ||
| Data Description and Summarization: | ||
| Select one of the following: | 3-4 | |
| Principles of Business Analytics | ||
| Statistics | ||
| Applied Statistics | ||
| Data Management - Structured: | ||
| Select one of the following: | 9-12 | |
| Business Computing and Information Technology and the Intelligent Enterprise and Database Systems and Data Warehousing | ||
| Fundamentals of Programming and Problem Solving and Object-Oriented Programming and Data Abstraction and Data Structures and Database Systems | ||
| Regression Models: | ||
| Select one of the following: | 3-4 | |
| Examining Economic Data and Models | ||
| Applied Regression Analysis in Business | ||
| Introduction to Statistical Modeling | ||
| Regression Analysis | ||
| Visualizing Data and Digital Dashboards: | ||
| STA 404 | Advanced Data Visualization | 3 |
| Track | ||
| Select a track of study 1 | 15 | |
| TRACK 1: BUSINESS ANALYTICS | ||
| Note: For Information and Cybersecurity Management majors, Information Systems majors, or Information Systems and Analytics majors with Information Systems track, 18 hours must not double count in the ICM major, IS major, or ISA major with IS track and Analytics Co-Major or business core. | ||
| Note: For STA majors, at least 18 hours must be courses not double counted toward the STA major. | ||
| Note that ISA 291 must be taken as the core option for this track. | ||
| Note: For Information Systems Minors, 9 hours must not double count for the minor. | ||
| Required Courses | ||
| Business Intelligence and Data Visualization | ||
| Managing Big Data | ||
| Introduction to Data Mining in Business | ||
| Select two of the following: | ||
| Concepts in Business Programming | ||
| Quantitative Analysis of Business Problems | ||
| Nonparametric Statistics | ||
| Statistical Monitoring and Design of Experiments | ||
| Business Forecasting | ||
| Topics in Business Analytics | ||
| Business Analytics Practicum | ||
| Statistical Programming | ||
| Introduction to Bayesian Statistics | ||
| Survey Sampling in Business | ||
| TRACK 2: PREDICTIVE ANALYTICS | ||
| Required Courses | ||
| Statistical Programming | ||
| Statistical Learning | ||
| Select two of the following: | ||
| Managing Big Data | ||
| Introduction to Bayesian Statistics | ||
| Analysis of Forecasting Systems | ||
| Select one of the following: | ||
| Optimization Modeling | ||
| Mathematical Modeling Seminar | ||
| Quantitative Analysis of Business Problems | ||
| Optimization | ||
| Stochastic Modeling | ||
| TRACK 3: GEOSPATIAL ANALYTICS | ||
| Note: Students who wish to also earn the GISci Certificate must take an additional 6 appropriate credit hours beyond the Analytics Co-Major requirements. | ||
| Required Courses | ||
| Geographic Information Systems | ||
| Advanced Geographic Information Systems | ||
| Advanced Systematic Geography | ||
| Select six hours of the following: | ||
| Python Programming for Geospatial Applications | ||
| GIScience Techniques in Landscape Ecology | ||
| Techniques and Applications of Remote Sensing | ||
GEO 460G | Tools | |
| Virtual Reality | ||
| Managing Big Data | ||
| Total Credit Hours | 33-38 | |
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In addition to the common core, each co-major is required to complete a particular track of study. These tracks reflect a focus on a particular area of application of analytics or advanced methods.