Training

Take advantage of additional learning opportunities while attending the conference - post-conference courses are now open to the public. Pass the word to your co-workers, they can come for just the post-conference training! All pre- and post-conference training will take place in Building F on the SAS Cary campus.

Modeling Trend, Cycles, and Seasonality in Time Series Data using PROC UCM

(Sunday, May 31; 1-5pm)

This half-day lecture teaches students how to model, interpret, and predict time series data using UCMs. The UCM procedure analyzes and forecasts equally spaced univariate time series data using the Unobserved Components Models (UCM).

This course is designed for business analysts who want to analyze time series data to uncover patterns such as trend, seasonal effects, and cycles using the latest techniques.

View the complete outline.

Forecasting with Limited Data - a Practical Approach

(Sunday. May 31, 1-5 pm) (provisional)

This half-day seminar teaches students statistical techniques to incorporate a structured judgmental approach for analyzing time series and generating forecasts in support of practical applications. The the seminar firsts focuses on the theoretical construct of time-series data mining with a special emphasis on dimension reduction and similarity analysis in support of time series clustering. Second, the seminar coalesces the data mining techniques and panel series analyses by presenting an application designed to formulate introductory distributions and life-cycle curves for new or retiring products/markets/services.

This course is designed for professional forecasters and business analysts who need to forecast products or services with little history or that are near the end of their life cycles. In these situations traditional time series forecasting methods may not perform well.

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Forecasting Using SAS Forecast Server Software

(Wednesday-Thursday, June 3-4; 9am-5pm)

This two-day class prepares you to generate large volumes of forecasts automatically using the SAS Forecast Studio interactive interface. You learn to manage default settings to improve forecast accuracy, produce forecasts and reconcile them across hierarchies, and produce forecasts in an appropriate form for integration with a business intelligence solution.

The course is designed for business analysts and others who want to create business forecasts using SAS Forecast Server. The course is appropriate for analysts in any industry, including retail, financial services, manufacturing, and pharmaceuticals.

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Using SAS High-Performance Forecasting Software

(Wednesday-Friday, June 3-5; 9am-5pm)

This three-day course enables you to make accurate forecasts quickly and automatically, giving you the power to confidently plan your business operations. This course focuses on the following areas: creating programs that provide forecasts as output files or SAS data sets and structuring the programs and output so that they can be incorporated into a corporate forecasting system; assessing forecast performance and making decisions about the adequacy of initial forecasts, as well as the adequacy of forecasts that are being dynamically produced; and manually overseeing forecasting or devising automated strategies to determine when a forecast model should be updated. The course teaches how to create customized selection lists and events.

This course is designed for professional forecasters and power users who need to produce forecasts for large numbers of time series and need to customize their Forecast Server environment.

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Forecasting Using SAS Software: A Programming Approach

(Wednesday-Friday, June 3-5; 9am-5pm)

This three-day course teaches analysts how to use SAS/ETS software to create forecasting models, evaluate the model for accuracy, and forecast future values using the model.

The course is intended for scientists, engineers, and analysts who have the responsibility of forecasting for their organizations. Students are expected to have some knowledge of analytics coursework such as applied statistics, statistical modeling, or data mining and domain knowledge in an application area such as energy production, manufacturing, or a scientific discipline.

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Introduction to Applied Econometrics

(Wednesday-Friday, June 3-5; 9am-5pm)

This three-day course focuses on the development and use of single-equation econometric models that enable analysts to better understand their economic/business landscape and to improve their ability to make sound economic/business forecasts.

The course is intended for academicians, economists, forecasters, and government and business analysts.

View the complete outline.