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Our conference lineup for 2012

Here at SAS Publishing, we’ve started the new year off with a bang, particularly when it comes to conferences. We’re attending a number of new shows in addition to the usual lineup this year. Visit our booth, meet our authors, check out our new and forthcoming titles, and talk with

SAS Events
Waynette Tubbs 0
IFSUG Summit registration now open!

Are you a SAS professional working in the insurance or financial services industry? Are you looking for a place where you can talk with others who work in the those industries? Would you like to get together and network, face-to-face, or share ideas and best practices for using SAS? There is now a SAS Users Group just for you;

Rick Wicklin 0
Reading ALL variables INTO a matrix

The SAS/IML READ statement has a few convenient features for reading data from SAS data sets. One is that you can read all variables into vectors of the same names by using the _ALL_ keyword. The following DATA steps create a data set called Mixed that contains three numeric and

Data Visualization
Sanjay Matange 0
The more the merrier

Often it is useful to view multiple responses by a common independent variable all in the same plot.  SGPLOT procedure and GTL support the ability to view two responses, one each on the Y and Y2 axes by one independent variable (X) in one graph.  Yes, you can also have X

Rick Wicklin 0
Overlay density estimates on a plot

A recent question on a SAS Discussion Forum was "how can you overlay multiple kernel density estimates on a single plot?" There are three ways to do this, depending on your goals and objectives. Overlay different estimates of the same variable Sometimes you have a single variable and want to

Learn SAS
Sean Gargan 0
SAS OnDemand and great practice data

You know the old joke about the guy who jumps into a taxi and asks the driver, “Do you know how to get to Carnegie Hall?” and the driver replies, “Practice, practice, practice”.  Well SAS OnDemand may not be your ticket to Carnegie Hall but it’s a great practice environment

Data Visualization
Sanjay Matange 0
Custom confidence intervals

Recently a user posted a question on the SAS/GRAPH and ODS Graphics Forum about drawing a plot with custom confidence intervals .  The user has a simple data set with category, response (mean) and custom lower and upper confidence intervals.  The data looks like this: Robert Allison provided the code (proc gplot +

Rick Wicklin 0
How to lie with a simulation

In my article on Buffon's needle experiment, I showed a graph that converges fairly nicely and regularly to the value π, which is the value that the simulation is trying to estimate. This graph is, indeed, a typical graph, as you can verify by running the simulation yourself. However, notice

Data Visualization
Sanjay Matange 0
In good company

A recent post on the SAS website shows the SAS Annual Revenue History.  It would be interesting to see how we could create such a graph using SG procedures, and how we could add more information and interest in the presentation.  So, I started with the basic informaiton on the annual revenues provided,

Rick Wicklin 0
Simulation of Buffon's needle in SAS

Buffon's needle experiment for estimating π is a classical example of using an experiment (or a simulation) to estimate a probability. This example is presented in many books on statistical simulation and is famous enough that Brian Ripley in his book Stochastic Simulation states that the problem is "well known

Data Visualization
Sanjay Matange 0
Simply useful

Let us ring in the new year with something simple and useful. A recent question by a user over the holidays motivated this article on what is likely a commonly used graph.  We want to compare the preformance of two categories along with a third measure.  This could be something like "How

Rick Wicklin 0
New 2012 resolutions for my blog

Hello, 2012! It's a New Year and I'm flushed with ideas for new blog articles. (You can also read about The DO Loop's most popular posts of 2011.) The fundamental purpose of my blog is to present tips and techniques for writing efficient statistical programs in SAS. I pledge to

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