MG 391 Data Analytics for Leaders

Lecture Hours: 6
Credits: 6

Determine the best tool for turning data into a competitive advantage and to apply different models to data analysis. Explains how to make predictions using data. Understand tools and frameworks to build predictive models. Use business analytics to interpret and analyze data to serve customers better. Focuses on managerial decision making, machine learning and its business applications.

Prerequisite: Admitted into Applied Baccalaureate Program; completion of AAS program; or consent of instructor.
Student Learning Outcomes:

Describe different types of data and their utility
Apply tools & techniques to perform data analysis 
Make predictions using data to inform strategy
Evaluate complex business decisions in uncertain settings

Content Outline

Types of Data
- Data types and sources
- Collection methods and tools
- Data security
Technical Skills for Data Analysis
- Correlation and causation
- Regression analysis
Types of Analysis
- Descriptive, diagnostic, predictive, prescriptive
- Tools for analysis
- Correlation and causation
Data informed practice and decision-making
- Data visualization and interpretation
- Forecasting
Ethical use of data in persuasive communication
- Optimization Models
- Decisions Trees