Time Series & Predictive Analysis for Business

Catalog description

This course provides an introduction to time series analysis and forecasting for students with little background in mathematics and statistics. The course presents the theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts. The course offers exercises from diverse disciplines including healthcare, environmental studies, engineering, and finance in more than 50 programming algorithms using R that illustrate the theory and practicality of forecasting techniques in the context of time-oriented data. The course teaches methods of data analysis and their application to real-world data sets and also serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. This course appeals to business professionals and computer science and statistics graduates, as well as graduate students in MBA programs. Required course.