Schedule of Classes

Introduction to descriptive and inferential statistics with an emphasis on business applications. Topics covered include computation and application of descriptive measures, probability distributions, sampling, confidence intervals, hypothesis testing, correlation, and simple linear regression.

Continuation of Q M 262. Topics covered include tests of hypotheses, correlation, time series, and multiple regression analysis with specific application to problems in business and economics. Computer software will be used extensively in regression analysis.

Introduction to managerial statistical tools in descriptive and predictive analytics with an emphasis on statistical learning. Topics covered include regression analysis, simulation, decision analysis, and data mining. Extensive use of computer software for model building and analysis for making better business decisions. Cross-listed with Q M 564.

Introduction to managerial statistical tools in descriptive and predictive analytics with an emphasis on statistical learning. Topics covered include regression analysis, simulation, decision analysis, and data mining. Extensive use of computer software for model building and analysis for making better business decisions. Cross-listed with Q M 426. The graduate level course will have additional requirements beyond those of the undergraduate course.