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Data Visualization
Sanjay Matange 0
Beer, diapers and heat map

The parable of beer and diapers is often related when teaching data mining techniques.  Whether fact or fiction, a Heat Map is useful to view the claimed associations.  A co-worker recently enquired about possible ways to display associations or dependency between variables.  One option is to show the dependency as a node

Advanced Analytics
Waynette Tubbs 0
Friday's Innovation Inspiration - Big data

Big data is one of the hottest topics in business. When you hear those words - BIG Data - you almost surely think of: HUGE financial services firms scoring terabytes of historical and current risk data GLOBAL telecommunications companies mining petabytes of structured and unstructured data INTERNATIONAL retailers repricing hundreds of thousands of products across

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

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

Data Visualization
Sanjay Matange 0
Comparative density plots

Recently a user posted a question on the SAS/GRAPH and ODS Graphics Communities page on how to plot the normal density curves for two classification levels in the same graph. We have often seen examples of a  distribution plot of one variable using a histogram with normal and kernel density curves.  Here is a simple example: Code Snippet:

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

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

Data Visualization
Sanjay Matange 0
Nested graphs

Here are a couple of bar charts showing the city mileage of cars by Type and Origin using the SGPLOT procedure from the sashelp.cars dataset. title 'Vehicle Mileage by Type'; proc sgplot data=cars; format mpg_city 4.1; vbar type / response=mpg_city stat=mean datalabel; xaxis display=(nolabel); run; title 'Counts by Country'; proc sgplot

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

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