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Mike Gilliland 0
IBF conference and The BFD book signing

I love dogs. Not to the extent that Rick Santorum has to be concerned. And not to the extent of actually having a dog as a pet. But man-dog love has become an issue in the 2012 US presidential campaign, and I thought The BFD readers should know my stance

Advanced Analytics
Rick Wicklin 0
What is Mahalanobis distance?

I previously described how to use Mahalanobis distance to find outliers in multivariate data. This article takes a closer look at Mahalanobis distance. A subsequent article will describe how you can compute Mahalanobis distance. Distance in standard units In statistics, we sometimes measure "nearness" or "farness" in terms of the

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New Business Intelligence book will help many SAS users

Building Business Intelligence Using SAS: Content Development Examples by Tricia Aanderud and Angela Hall just published this month. This highly anticipated book—called “a must read for anyone using SAS® BI”* —is a quick-start guide that will help users move quickly from using only one of the SAS BI Clients to

Analytics
Melissa Savage 0
Analytics helping transportation officials get the job done in tight financial times

The American Association of State Highway Transportation Officials recently released a top 10 list of transportation issues that will be “talked, written or tweeted and legislated about” in 2012.   As expected, funding constraints and Congressional action on reauthorization appear on the list but the group also notes that natural disaster

Advanced Analytics
Rick Wicklin 0
Use the Cholesky transformation to correlate and uncorrelate variables

A variance-covariance matrix expresses linear relationships between variables. Given the covariances between variables, did you know that you can write down an invertible linear transformation that "uncorrelates" the variables? Conversely, you can transform a set of uncorrelated variables into variables with given covariances. The transformation that works this magic is

Mike Gilliland 0
Forecasting fashion apparel (Part 3)

Some ideas sound great (combining chocolate with peanut butter) and turn out great (Reese's Peanut Butter Cup).  Some ideas sound great (getting a face lift) but turn out bad (Kenny Rogers, Greta Van Susteren). Some ideas sound bad (a Run-DMC / Aerosmith duet) but turn out great ("Walk This Way").   Some ideas sound bad (letting

Rick Wicklin 0
How to access SAS sample programs

Have you ever wanted to run a sample program from the SAS documentation or wanted to use a data set that appears in the SAS documentation? You can: all programs and data sets in the documentation are distributed with SAS, you just have to know where to look! Sample data

Mike Gilliland 0
Forecasting fashion apparel (Part 2)

Have you noticed the annoying stock art they put on The BFD blog header? All I can think of is "If those idiots only used SAS Forecast Server, they wouldn't have to draw graphs all over their window panes just to do forecasting." It must really p.o. the housekeeping staff at that

Rick Wicklin 0
Random number seeds: Only the first seed matters!

The other day I encountered the following SAS DATA step for generating three normally distributed variables. Study it, and see if you can discover what is unnecessary (and misleading!) about this program: data points; drop i; do i=1 to 10; x=rannor(34343); y=rannor(12345); z=rannor(54321); output; end; run; The program creates the

Data Visualization
Dan Heath 0
A (tool)tip for band plots

Recently, I had a discussion with a user concerning the volume of imagemap data generated for an interactive,  web-based visual contain a large number of graphs. The large amount of imagemap data was causing problems with the current version of their web browser. The graphs consisted of either bar charts

Mike Gilliland 0
Forecasting fashion apparel

Ten years ago I spent some time in women's undergarments*, as Director of Forecasting at Sara Lee Intimate Apparel (now Hanesbrands).  Sure, it sounds glamorous -- product posters on our office walls, quarterly runway shows of new products, and partying with the full-figured Playtex models (some of whom were fuller than I figured). 

Rick Wicklin 0
Detecting outliers in SAS: Part 2: Estimating scale

In a previous blog post on robust estimation of location, I worked through some of the examples in the survey article, "Robust statistics for outlier detection," by Peter Rousseeuw and Mia Hubert. I showed that SAS/IML software and PROC UNIVARIATE both support the robust estimators of location that are mentioned

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3 things every elementary statistics student should know

We’ve just published Chris Olsen’s Teaching Elementary Statistics with JMP, which offers the latest research on best practices and how JMP can facilitate teaching statistics. To mark the book’s publication, we asked Chris to tell us the top three things every elementary statistics student should know. Statistics is about numbers

Mike Gilliland 0
For the love of forecasting

Love can make a person do bad, dangerous, stupid, and irresponsible things.  Love of country can make a politician stray from his wife. Love of Pepsi can make a pop musician lose his hair in a pyrotechnics-gone-bad commercial. Love of acting can make academy award winners accept starring roles in Ishtar. And for

Rick Wicklin 0
Explaining coincidence

I was on vacation when a family member sidled up to me. "Rick, you're a statistician..." he began. I knew I was in trouble. He proceeded to tell me the story of Joseph "Newsboy" Moriarty, a New Jersey mobster who rose to prominence and became known as the bookie who

Rick Wicklin 0
Constants in SAS

Statistical programmers often need mathematical constants such as π (3.14159...) and e (2.71828...). Programmers of numerical algorithms often need to know machine-specific constants such as the machine precision constant (2.22E-16 on my Windows PC) or the largest representable double-precision value (1.798E308 on my Windows PC). Some computer languages build these

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