My previous post pondered the term disestimation, coined by Charles Seife in his book Proofiness: How You’re Being Fooled by the Numbers to warn us about understating or ignoring the uncertainties surrounding a number, mistaking it for a fact instead of the error-prone estimate that it really is. Sometimes this fact appears to
Many people know that the SAS/IML language enables you to read data from and write results to multiple SAS data sets. When you open a new data set, it is a good programming practice to close the previous data set. But did you know that you can have two data
Imagine that you’re a large retail firm, in need of projecting sales for the next few months. With the right analytical solution, it can literally take just seconds to have a forecast in place. You drag and drop some variables and can figure out exactly which ones are underlying factors
