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.

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
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 404Advanced Data Visualization3
Select a track of study 115
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
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
Stochastic Modeling
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
Virtual Reality
Managing Big Data
Total Credit Hours33-38

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.