This intermediate-level course will explain tools and frameworks to deliver data to improve organizational performance and explain the relationship between assessment and strategy in real-world decision making.

This course discusses data-driven decision making across a variety of industries while offering recommendations for decision-making based on data analytics for each sector. 

This course will introduce the different types of decisions made in an organizational setting, why quantitative analytics is important, and how data quality can affect decision making. It highlights appropriate quantitative methods and ways to ensure quality and accuracy through research design.

This intermediate-level course introduces the basics of quality management, explains the difference between quality control and quality assurance, provides methods for application of analysis, and shows different applications of the Seven Basic Quality Tools. 

This intermediate-level course examines statistics as a managerial tool. It also looks at common graphical representations of data and how these can be effective tools to explain situations and support persuasive arguments for a course of action

This intermediate-level course describes, evaluates, and analyzes different statistical techniques and their real-world limitations and benefits. It features crossover analysis, break-even analysis, cluster analysis, decision tree analysis as well as an introduction to regression.