Training Process in Sas - 1207 Words

Onsite training SAS Onsite Training Service provides you the opportunity to bring SAS software training directly to your organization. With education experts from SAS, you can train your employees in a familiar environment, saving your money for training instead of travel. On-site training is designed specifically for your organizations when you need: * group SAS software training * flexible training schedules * lower employee travel costs On-site courses combine lectures, software demonstrations, hands-on computer workshops, and course notes that result in the best learning experience possible. In addition, we will provide a copy of the course notes to each attendee. Data Manager * SAS Programming Introduction: Basic†¦show more content†¦ration for Data Mining DMDP * Exploratory Analysis for Large and Complex Problems BEAP * Managing SAS Analytical Models Using SAS Model Manager MMUS Forecaster * Business Forecasting Using SAS: A Point-and-Click Approach FETS * Forecasting Using SAS Software: A Programming Approach FETSP * Forecasting Using SAS Forecast Server Software FSTU21 * Using SAS High-Performance Forecasting Software HPF * Modeling Trend, Cycles, and Seasonality in Time Series Data Using PROC UCM LWBARS * Stationarity Testing and Other Time Series Topics LWBADD Market Research * Applied Clustering Techniques CLUS92 * Design of Experiments for Direct Marketing DOEF92 Operations Researcher * Building and Solving Optimization Models with SAS/OR OROP92 * Statistical Process Control Using SAS/QC Software SPCQC9 JMP Analyst * JMP Software: Statistical Data Exploration JDEX7 * JMP Software: ANOVA and Regression JANR7 * JMP Software: Classic Design of Experiments JDRS7 * JMP Software: Custom Design of Experiments JMDOE7 * JMP Software: Analysis of Dose-Response Curves with JMP JDOSE7 * JMP Software: Introduction to Categorical Data Analysis JCAT7 * JMP Software: Statistical Quality Control JSQC7 * Mixture Design of Experiments Using JMP BJMX7 ------------------------------------------------- SAS Solution Lines Activity-Based Management * Activity-Based Management Concepts * ABC Modeling Using SAS Activity-BasedShow MoreRelatedFlow Chart1281 Words   |  6 PagesDraw a flow chart of any one function/process in your organization. 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For the function/process chosen, measure WIP and throughput and calculateRead MoreThe Sas Institute Is A Privately-Owned Software Company.1272 Words   |  6 PagesThe SAS Institute is a privately-owned software company. They focus on long term strategic partnerships alongside their customers to provide new and effective products. SAS’s revenue model for their data analytic software entails an annual licensing subscription, which includes all new updates to software and access customer support. This platform creates an emphasis on maintaining relationships between SAS and customers during and after development. At SAS Institute, they do not focus on â€Å"directRead MoreMotivating Employees Case Study705 Words   |  3 Pagesequally effective in the right situation. SAS Institute has gained a high reputation for their ability to motivate its employees with a balance of intrinsic and extrinsic motivation. How Does SAS motivate its employees? 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Since founded in 1976, they had been using the same organizational design. But withRead MoreThe Performance And Reward Management System1501 Words   |  7 Pagesfundamental to the success or failure of the performance management process, therefore, raters have been suggested to be fully trained to minimise potential errors in performance ratings (Biron, Farndale, Paauwe, 2011). Several rater training programs have been developed to enhance the quality of performance ratings, such as rater error training and frame-of-reference training (MacDonald Sulsky, 2009). Nevertheless, not all rater training programs have been equally successful, many researchers haveRead MoreLiterature Review On Seven Data Mining Techniques Essay1431 Words   |  6 Pages1.3 Literature Review on Seven Data Mining Techniques 1.3.1 K-Nearest Neighbor Classifiers (KNN) Given a positive number K and an unknown sample, a KNN classifier searches the K closest observations in training set to the unknown sample. It then classifies the unknown sample into the class with the smallest distance. The advantage of KNN is that it does not need to estimate the relationship between the response and the predictors (Shmueli, et al. 2016), while this method is dramatically