Analytics Co-Major

The Department of Statistics offers an analytics co-major. 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.

There are two track options that can be taken through this co-major, either Business Analytics or Predictive Analytics, with the course and track requirements listed below.

Program Requirements

Core Coursework (18 or 19 credit hours):
1. Data description and summarization.  (Select one)
      ISA 205: Business Statistics (4) OR ISA 225: Principles of Business Analytics (3) OR STA 261: Statistics (4) OR STA 301: Applied Statistics (3) OR STA 368: Introduction to Statistics (4)
2. Data management-Structured:
     CSE148 Business Computing (3) AND ISA235 Information Technology and the Intelligent Enterprise (3) AND ISA245 Database Systems and Data Warehousing (3)
                        OR
  CSE174 Fundamentals of Programming and Problem Solving (3) AND CSE271 Object-Oriented Programming (3) AND CSE274 Data Abstraction and Data Structures (3) AND CSE385 Database Systems (3)
3. Regression models:(Select one)
ECO 311: Examining Economic Data and Models (3)
 ISA291 Applied Regression Analysis in Business
 STA363 Introduction to Statistical Modeling
 STA463 Regression Analysis 

4. Visualizing data and digital dashboards:
STA/IMS404 Advanced Data Visualization (3)

*Must be taken as the core option for track 1.
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.

Track 1: Business Analytics (Note: For IS majors, at least 18 hours beyond the business core must be courses not counted toward the IS major)

Required: (6 hours) - Note that ISA291 must be taken as the core option for this track
ISA 401: Business Intelligence and Data Visualization (3)
ISA414 Managing Big Data (3)
ISA491 Data Mining (3)

Electives:
Must take two of these (6 hours)

ISA 281 Concepts in Business Programming (3)
ISA 321 Quantitative Analysis of Business Problems (3)
ISA/STA 333 Nonparametric Statistics (3)
ISA/STA 365 Statistical Quality Control (3)
ISA/STA 432 Survey Sampling in Business (3)
ISA 444 Business Forecasting (3)
ISA 480 Topics in Decision Sciences (1-3; maximum 3)
STA 402 Statistical Programming (3)
STA 427 Introduction to Bayesian Statistics (3)

Track 2: Predictive Analytics

Required: (15 hours)
STA402 Statistical Programming
STA427 Bayesian Methods
STA467 Statistical Learning
STA 427 Managing Big Data

Select one of the Following
ISA 321: Quantiative Analysis of Business Problems (3)
MTH 432: Optimization (3)
CSE 372: Stochastics Modeling (3)

Track 3: Geospatial Analytics 

Required Courses
GEO 441: Geographic Information Systems (3)
GEO 442: Advanced Geographic Information Systems (3)
GEO 460: Advanced Systematic Geography (3)

Select six hours of the following
GEO 443: Python Programming for ArcGIS (3)
GEO 444: GIScience Techniques in Landscape Ecology (3)
GEO 448: Techniques and Applications of Remote Sensing (3)
GEO 460G: Tools (3)
IMS 461: Advanced 3D Visualization and Simulation (3)
ISA 414: Managing Big Data (3)

For course descriptions please see the bulletin pages for CSE, ISA and STA.