Q M 262 - Quantitative Analysis I (3.0 hours)

Core Curriculum: QR

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.

Prerequisite: MTH 114 or higher.

Q M 263 - Quantitative Analysis II (3.0 hours)

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.

Prerequisite: Q M 262

Q M 369 - Topics in Quantitative Methods (3.0 hours)

Topics of special interest which may vary each time course is offered. Topic stated in current Schedule of Classes. May be repeated under different topics for a maximum of six hours.

Prerequisite: junior/senior standing.

Q M 426 - Business Forecasting (3.0 hours)

Introduction to forecasting, forecasting methods, features and differences using theoretical and practical knowledge gained about forecasting methods. Topics covered include regression analysis, time series analysis, understanding moving averages, exponential smoothing, autoregression and trend curves and to be able to use these modelling techniques to obtain forecasts. Cross-listed with Q M 526.

Prerequisite: Q M 263 and junior/senior standing.

Q M 464 - Decision Support Systems (3.0 hours)

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.

Prerequisite: Q M 263

Q M 498 - Independent Study in Quantitative Methods (1.0-3.0 hours)

Studies undertaken by academically qualified students under guidance of a faculty member. Open to Finance and Quantitative Methods Department majors only. May be repeated under different topics for a maximum of six hours.

Prerequisite: junior/senior standing; 2.5 cumulative grade point average; consent of Department Chair.

Q M 526 - Business Forecasting (3.0 hours)

Introduction to forecasting, forecasting methods, features and differences using theoretical and practical knowledge gained about forecasting methods. Topics covered include regression analysis, time series analysis, understanding moving averages, exponential smoothing, autoregression and trend curves and to be able to use these modelling techniques to obtain forecasts. Cross-listed with Q M 426. The graduate level course will have additional requirements beyond those of the undergraduate course.

Prerequisite: IME 511 or consent of Department Chair.

Q M 564 - Decision Support Systems (3.0 hours)

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.

Prerequisite: IME 511 or consent of Department Chair.

Q M 658 - Topics in Quantitative Methods (3.0 hours)

Topics of special interest which may vary each time the course is offered. Topic stated in current Schedule of Classes. May be repeated up to 9 hours under different titles/topics.

Q M 660 - Readings in Quantitive Methods (1.0-3.0 hours)

Individual readings for qualified students, under the guidance of a member of the faculty. Repeatable to a maximum of 3 credit hours.

Prerequisite: consent of instructor and director of graduate programs.