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 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.

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.