To introduce participants to a problem-driven approach to assembling, analyzing, and taking action on data. With the Problem-Plan-Data-Analysis-Conclusions (PPDAC) Cycle and Gartner’s Analytics Maturity Model (Descriptive → Diagnostic → Predictive → Prescriptive Analytics) as frameworks, fundamental concepts for the analysis of data will be covered, including descriptive statistics, visualizations, probability and distributions, confidence intervals, hypothesis testing, and regression. Knowledge of the “whys” behind these tools facilitates rigorous data-driven decision-making. The learning objectives of this course are:

1. To understand and execute the process of decision-making based on data;
2. To assemble, summarize, visualize, and analyze data arising in decision making; and,
3. To conceptualize and interpret models for diagnostic, predictive, and prescriptive analytics.

The instructional approach will combine theory and application. A computer with the rights to install software will be needed in each class (a smartphone/tablet will not suffice). Please note that necessary theoretical foundations will need to be covered to ensure appropriate application of these concepts in practice.