Uncategorized

Mike Gilliland 0
Why forecasts are wrong: Inadequate/unsound/misused software

A common mistake in bad or misused software is choosing a forecasting model based solely on the model’s “fit to history” (often referred to as “best fit” or “pick best” functionality). The software provides (or the forecaster builds) several competing models which are then evaluated against recent history. The model

Data for Good
Ross Kaplan 0
Is it fraud or abuse?

When discussing fraud and abuse, it often (very often) becomes a philosophical discussion of whether aberrant activities are fraudulent or abusive. The quick difference being that fraudulent is intentional and abuse is not.  The distinction quickly becomes an issue of legal and illegal as opposed to right and wrong. What

Rick Wicklin 0
The UNIQUE-LOC trick: A real treat!

When you analyze data, you will occasionally have to deal with categorical variables. The typical situation is that you want to repeat an analysis or computation for each level (category) of a categorical variable. For example, you might want to analyze males separately from females. Unlike most other SAS procedures,

Mike Gilliland 0
Flash3: Report from Analytics2011 in Orlando

Of course, forecasting the stock market is not perfectly analogous to forecasting demand for a product.  The asking price for a stock is largely "anchored" by the price of its most recent trades.  While market values may appear to randomly drift up and down, or in a general direction, we generally

Mike Gilliland 0
Flash2: Report from Analytics2011 in Orlando

In this second of three flash reports from last week's Analytics2011 conference, we hear about a favorite topic of mine -- the relationship between demand volatility and forecastability. Rob Miller of Avantor Performance Materials, on Forecastability and Demand Volatility The "comet chart," illustrating the relationship between demand volatility and forecast

Rick Wicklin 0
Video: Calling R from the SAS/IML Language

In SAS/IML 9.22 and beyond, you can call the R statistical programming language from within a SAS/IML program. The syntax is similar to the syntax for calling SAS from SAS/IML: You use a SUBMIT statement, but add the R option: SUBMIT / R. All statements in the program between the

Learn SAS
Shelly Goodin 0
SAS author's tip: generating a dagger

This week's featured tip is from master SAS user Art Carpenter and his classic book Carpenter's Complete Guide to the SAS REPORT Procedure. In his review for the book, Rick Mitchell-senior systems analyst at Westat-said "I am green with envy for the newest generation of SAS programmers because I wish that I had had this book in

Michael Newkirk 0
Is manufacturing dead in America?

I was privileged to attend the National Association of Manufacturers (NAM) Board of Directors meeting in Washington D.C. recently. Attended by some 300 senior executives of American Manufacturing companies, it was like a who’s-who in brand names anyone would recognize. NAM is a very big influencer of public policy on

Learn SAS
Shelly Goodin 0
What’s behind our orange covers

It’s bold, autumnal, and adorns team uniforms, frozen desserts, and hair. Wherever orange is used, it makes a statement.  With changing leaves and Halloween approaching, it’s appropriate to call attention to fall colors and covers. For this post, I rounded up all of the orange SAS book titles that I

Data Management
Kelly Levoyer 0
What's the news?

The Premier Business Leadership Series in Orlando was the backdrop for a number of news announcements from SAS. Here's a rundown: 1. Big Data research A new survey has found that organizations with formal data management strategies derive more value from data assets and outperform competitors. The survey, Big Data:

1 252 253 254 255 256 311