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SAS/ETS

Title Level Training Formats
Introduction to Applied Econometrics Business Knowledge Series
This course, the first of two, 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. Through hands-on exercises, participants gain knowledge of the practical elements of applied econometric analysis. The overall aims are to sharpen the quantitative, statistical, and analytical skills of participants in dealing with problems and issues related to business and economics as well as to improve communication skills in reporting findings to decision makers.

2 Fundamental Classroom
Advanced Topics in Applied Econometrics Business Knowledge Series
This sequel to Introduction to Applied Econometrics focuses on intermediate/advanced topics in working with econometric models. This course will enable analysts to better understand their economic/business landscape and to improve their ability to make sound forecasts. Through applications, participants gain knowledge of the practical elements of applied econometric analysis. The overall aims are to sharpen the quantitative, statistical, and analytical skills of participants in dealing with problems and issues related to business and economics as well as to improve communication skills in reporting findings to decision-makers.

3 Intermediate Classroom
Electric Load Forecasting: Fundamentals and Best Practices Business Knowledge Series
This course introduces electric load forecasting from both statistical and practical aspects using language and examples from the power industry. Through conceptual and hands-on exercises, participants experience load forecasting for a variety of horizons from a few hours ahead to 30 years ahead. The overall aims are to prepare and sharpen the statistical and analytical skills of participants in dealing with real-world load forecasting problems and improve their ability to design, develop, document, and report sound and defensible load forecasts.

According to statistics gathered on the first five offerings, this course was highly rated by students who ranged from new graduates with no industry or SAS experience to forecasting experts with over 30 years of industry experience and over 20 years of SAS programming background. The students represented all sectors of the industry: G&T, ISO, distribution companies, REPs, IOU, co-op, municipal, regulatory commission, and consulting firm. Titles of the participants ranged from analyst, engineer, manager, to director and vice president.

For advanced topics, pair this course with Electric Load Forecasting: Advanced Topics and Case Studies. The two courses are offered on contiguous days.

3 Intermediate Classroom
Electric Load Forecasting: Advanced Topics and Case Studies Business Knowledge Series
This hands-on workshop is open to those who attended the Electric Load Forecasting: Fundamentals and Best Practices course. This course includes lecture and hands-on lab exercises that explore advanced topics in electric load forecasting.

4 Expert Classroom
Establishing Causal Inferences: Propensity Score Matching, Heckman's Two-Stage Model, Interrupted Time Series, and Regression Discontinuity Models Business Knowledge Series
This course introduces some methods commonly used in program evaluation and real-world effectiveness studies, including two-stage modeling, interrupted time-series, regression discontinuity, and propensity score matching. These methods help address questions such as: Which medicine is more effective in the real world? Did an advertising program have an impact on sales? More generally, are the changes in outcomes causally related to the program being run?

3 Intermediate Classroom e-Learning
Modeling Trend, Cycles, and Seasonality in Time Series Data Using PROC UCM Business Knowledge Series
This class teaches 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).

3 Intermediate Classroom Live Web Classroom
Using SAS Forecast Server Procedures
This course teaches you how to create and manage a complete forecasting system using the SAS Forecast Server procedures, giving you the power to confidently plan your business operations.

3 Intermediate Classroom Live Web Classroom
Time Series Modeling Essentials
The course covers the fundamentals of modeling time series data, and focuses on the applied use of the three main model types used to analyze univariate time series: exponential smoothing, autoregressive integrated moving average with exogenous variables (ARIMAX), and unobserved components (UCM).

3 Intermediate Classroom Live Web Classroom
Forecasting Using SAS Software: A Programming Approach
This course teaches analysts how to use SAS/ETS software to diagnose systematic variation in data collected over time, create forecast models to capture the systematic variation, evaluate a given forecast model for goodness-of-fit and accuracy, and forecast future values using the model. Topics include Box-Jenkins ARIMA models, dynamic regression models, and exponential smoothing models.

4 Expert Classroom Live Web Classroom
State Space Modeling Essentials Using the SSM Procedure in SAS/ETS New
This course covers the fundamentals of building and applying state space models using the SSM procedure (SAS/ETS). Students are presented with an overview of the model and learn advantages of the State Space approach. The course also describes fundamental model details, presents some straightforward examples of specifying and fitting models using the SSM procedure, and considers estimation in SSM, focusing on the Kalman filter and related details. The course concludes with a variety of SSM modeling applications, focused mainly on time series.

4 Expert Classroom Live Web Classroom
Stationarity Testing and Other Time Series Topics Business Knowledge Series
This course addresses a basic question in time series modeling and forecasting: whether a time series is nonstationary. This question is addressed by the unit root tests. One of the most common tests, the Dickey-Fuller test, is discussed in this lecture.

3 Intermediate Classroom Live Web Classroom e-Learning
Statistics 2: ANOVA and Regression
This course teaches you how to analyze continuous response data and discrete count data. Linear regression, Poisson regression, negative binomial regression, gamma regression, analysis of variance, linear regression with indicator variables, analysis of covariance, and mixed models ANOVA are presented in the course.

3 Intermediate Classroom Live Web Classroom e-Learning