Well, Wall Street cares so much about making fast decisions that it is laying dedicated high-speed lines so that the data for program trades can be processed faster and orders executed more quickly. If Wall Street can do all this in milliseconds, won’t it make a difference to you to
Systems engineer Jami Hampton opened the autumn 2011 series of live Mastering JMP webcasts to 600 JMP users who wanted to learn how to find a good multiple regression model using the JMP Fit Model platform. Jami's PowerPoint presentation and videos of her demo are available. Jami used data and
When working with users new to JMP, I find it helpful to have a simple process to guide statistical discovery. We statisticians could debate the process of statistical discovery for a long time, but I find the process presented in Figure 1 works for most situations. Assuming we have already
The autumn lineup of live Mastering JMP webcasts is set. And if you are one of the 2,000+ JMP users who attended a live webcast during the first half of 2011, you'll notice some new topics: • Sept. 29: Finding the Best Predictive Model for Your Data • Oct. 6:
Gordon Linoff has been a self-starter in many ways. To name a few, he, along with Michael Berry, founded Data Miners Inc. in 1998. Gordon was also one of the first experts who SAS looked to in the 1990s to start the ever-popular SAS Business Knowledge Series. He has consulted for a wide
SAS® Structural Equation Modeling for JMP® is a new application that enables researchers to use SAS and JMP to draw models by using an interface that is built on the SAS/STAT® CALIS procedure. To create models in SAS Structural Equation Modeling for JMP, you simply drag variables into the diagram
When building models to predict a binary outcome variable, such as respond or not respond, the proportion in the desired category (respond) may be low. For example, in direct mail campaigns the response rate is often 1% or lower. In such cases, a predictive model is likely to learn how
As data volumes continue to grow, analysts, business users and students must rely on increasingly sophisticated techniques to extract meaningful, actionable information from their data. JMP is proof that they won’t have to sacrifice ease of use for predictive power: With JMP, popular data mining and forecasting tools are accessible
If you missed my live SAS TALKS webinar on June 23 titled Consider an Analytic Center of Excellence (and Other Ways to Create More Analytic Bandwidth), you can now watch it on demand. In addition, the slides I presented are now available to any who are interested in Analytic Centers
Systems engineer Mary Loveless and I have been barraged with requests to repeat her May 26 live Mastering JMP webcast on risk analysis. Rather than wait until schedules and advertising for a new webcast converge, I divided her demo into three sections for you to watch whenever you want. In