My elderly mother enjoys playing Scrabble®. The only problem is that my father and most of my siblings won't play with her because she beats them all the time! Consequently, my mother is always excited when I visit because I'll play a few Scrabble games with her. During a recent
I've previously described ways to solve systems of linear equations, A*b = c. While discussing the relative merits of the solving a system for a particular right hand side versus solving for the inverse matrix, I made the assertion that it is faster to solve a particular system than it
When I was at the Joint Statistical Meetings (JSM) last week, a SAS customer asked me whether it was possible to use the SGPLOT procedure to produce side-by-side bar charts. The answer is "yes" in SAS 9.3, thanks to the new GROUPDISPLAY= option on the VBAR and HBAR statements. For
At the SAS/IML Support Community, a SAS/IML programmer recently asked how to find "the root of a complicated equation." That's a huge question, and many papers and books have been written on the topic of root-finding, also known as finding the zeros of a function. Everyone has favorite techniques for
One of the great innovations with SAS 9.3 is the focus on ODS statistical graphics. "Wait a minute," you're thinking, "weren't ODS graphics added in SAS 9.2?" Yes, that's true. But with SAS 9.3 there is even more capability: more analytical SAS procedures support the graphs, and there are more
I've written about how to add a diagonal line to a scatter plot by using the SGPLOT procedure in SAS 9.2. The main idea (use the VECTOR statement) is easy enough, but writing a program that handles a line with any slope requires some additional effort. But now SAS 9.3
Here are a few new interface and graphics changes that every SAS programmer should know about SAS 9.3: HTML is now the default output destination when you run the SAS windowing environment. This means that tables and graphs appear in an HTML document instead of the classic LISTING destination. Of
As I was reviewing notes for my course "Data Simulation for Evaluating Statistical Methods in SAS," I realized that I haven't blogged about simulating categorical data in SAS. This article corrects that oversight. An Easy Way and a Harder Way SAS software makes it easy to sample from discrete "named"
Jittering. To a statistician, it is more than what happens when you drink too much coffee. Jittering is the act of adding random noise to data in order to prevent overplotting in statistical graphs. Overplotting can occur when a continuous measurement is rounded to some convenient unit. This has the
In my statistical analysis of coupons article, I presented a scatter plot that includes the identity line, y=x. This post describes how to write a general program that uses the SGPLOT procedure in SAS 9.2. By a "general program," I mean that the program produces the result based on the
Readers' comments indicate that my previous blog article about computing the area under an ROC curve was helpful. Great! There is another common application of numerical integration: finding the area under a density estimation curve. This article provides an overview of density estimation and computes an empirical cumulative density function.
A reader commented to me that he wants to use the HISTOGRAM statement of the SGPLOT procedure to overlay two histograms on a single plot. He could do it, but unfortunately SAS was choosing a large bin width for one of the variables and a small bin width for the
SAS Enterprise Guide has about 150 options that you can customize in the Tools->Options window. With each release, the development team adds a few more options that have been asked for by customers, and they rarely decommission any existing options. It's getting quite crowded on some of those options windows!
Many people know that the SGPLOT procedure in SAS 9.2 can create a large number of interesting graphs. Some people also know how to create a panel of graphs (all of the same type) by using the SGPANEL procedure. But did you know that you can also create a panel
In a previous blog post, I showed how you can use simulation to construct confidence intervals for ranks. This idea (from a paper by E. Marshall and D. Spiegelhalter), enables you to display a graph that compares the performance of several institutions, where "institutions" can mean schools, companies, airlines, or
This morning I delivered a talk to visiting high school students at the SAS campus. The topic: using SAS to analyze Twitter content. Being teenagers, high school students are well familiar with Twitter. But this batch of students was also very familiar with SAS, as they all have taken SAS
While talking to fellow SAS users at SAS Global Forum 2011 this week, I'll be discussing how SAS programmers can "play" with social media data that they can access on Facebook and Twitter. I always refer people to my blog for more information, and so I've prepared this blog post
This week, I posted the 100th article to The DO Loop. To celebrate, I'm going to analyze the content of my first 100 articles. In December 2010, I compiled a list of The DO Loop's most-read posts, so I won't repeat that exercise. Instead, I thought it would be interesting
In a previous post, I described how to compute means and standard errors for data that I want to rank. The example data (which are available for download) are mean daily delays for 20 US airlines in 2007. The previous post carried out steps 1 and 2 of the method
I recently posted an article about representing uncertainty in rankings on the blog of the ASA Section for Statistical Programmers and Analysts (SSPA). The posting discusses the importance of including confidence intervals or other indicators of uncertainty when you display rankings. Today's article complements the SSPA post by showing how
Do you have many points in your scatter plots that overlap each other? If so, your graph exhibits overplotting. Overplotting occurs when many points have similar coordinates. For example, the following scatter plot (which is produced by using the ODS statistical graphics procedure, SGPLOT) displays 12,000 points, many of which
We're just under two months away from SAS Global Forum 2011, and I'm feeling pretty good. Oops, I shouldn't have said that. That's going to come back to bite me, I'll bet. But I've already checked off so much on my to-do list! First, I got myself invited to attend.
A colleague posted some data on his internal SAS blog about key trends in the US Mobile phone industry, as reported by comScore. He graciously shared the data so that I could create a graph that visualizes the trends. The plot visualizes trends in the data: the Android phone is
A colleague related the following story: He was taking notes at a meeting that was attended by a fairly large group of people (about 20). As each person made a comment or presented information, he recorded the two-letter initials of the person who spoke. After the meeting was over, he
The Junk Chart blog discusses problems with a chart which (poorly) presents statistics on the prevalence of shark attacks by different species. Here is the same data presented by overlaying two bar charts by using the SGPLOT procedure. I think this approach works well because the number of deaths is
It's almost 2011, so let's reflect on the top 11 posts (by number of visits in 2010) on this blog. Not all of these posts were written in 2010; in fact, some of these date back to 2007. But apparently they are oldies and goodies. 1. SAS 9.2 and SAS
My last post was a criticism of a statistical graph that appeared in Bloomberg Businessweek. Criticism is easy. Analysis is harder. In this post I re-analyze the data to present two graphics that I think should have replaced the one graphic in Businessweek. You can download the SAS program that
I am thankful to be a statistical programmer. When I wake up in the morning, I am eager to start my day. I love statistics, programming, and working at SAS, and I write my blog to share that joy. This a Golden Age for statistical programmers because theoretical ideas and
The Junk Chart blog discusses a potential problem that can arise in grouped bar charts when the two groups have vastly different ranges. One possible solution (which is discussed at the Junk Chart sister blog, Numbers Rule Your World) is to present the data back-back in what is sometimes called
Question: What do you get when you cross your Facebook friends with SAS analytics? Answer: Insight, probably more about yourself than anything else. You can tell a lot about yourself by looking at your friends. And I'll bet that so can Facebook and those who advertise on it. Data from
