DATA TO DECISIONS

GENBUS 656

An introduction to predictive modeling for business applications beginning with some of the foundations. Leads to development of linear regression and classification models, and discussion of building models for prediction. Topics include selection, regularization, and the bias-variance tradeoff.

GENBUS 207

Enables you to understand and apply useful approaches to analyzing and presenting data to support business decision making. Emphasis on applications of predictive and prescriptive analytics. Predictive approaches use historical data to infer relationships and forecast future outcomes. Prescriptive methods formulate decision models to identify choices that are optimal with respect to a desired, measurable outcome. Provides experience integrating diverse data sources, modelling uncertainty, and visualizing key insights.

GENBUS 306

Development of quantitative intuition through practical applications and use of analysis tools. Specifically, emphasis will be on how to manage, summarize, explore, and visualize databases. The essentials of probability will be introduced and applied to decision problems where there is uncertainty. Emphasis on hypothesis testing and regression analysis and include an introduction to simulation methods. Throughout, attention will be paid to effective communication of data analysis. The use of business cases will connect the course material to both real world settings and recent advances in data analysis, including big data and data mining.

GENBUS 206

Learn basic business statistical skills to comprehend business reports, and to calculate statistical findings from business data using Excel. Understand simple probability calculations and how to apply probability to specific business uncertainties. Build capability to use simple statistical models and tests to estimate business variables of interest, and learn about predictive relationships between variables. Become comfortable using Excel for data manipulation, data analytics, and data visualization. Apply statistical analysis to address business issues.

GENBUS 705

A compact primer in statistics and an introduction to programming as a foundation for data-driven business analyses. The first part covers elementary concepts such as random variables, probability distributions, estimation, and ordinary least-squares regression. In the second part, the course exposes students to Python and R programming, including numerical and statistical packages that are relevant for practical applications in business.