Last year, I wrote more than 100 posts for The DO Loop blog. The most popular articles were about SAS programming tips for data analysis, statistical analysis, and data visualization. Here are the most popular articles from 2019 in each category. SAS programming tips Create training, testing, and validation data
The Rise of Skywalker, the final movie in the third set of the three Star Wars trilogies, will finally be released tomorrow (December 20, 2019). That's 9 movies, in about 42 years. And, if the first movies aren't still fresh in your mind (or perhaps you weren't even born when
A 2-D "bin plot" counts the number of observations in each cell in a regular 2-D grid. The 2-D bin plot is essentially a 2-D version of a histogram: it provides an estimate for the density of a 2-D distribution. As I discuss in the article, "The essential guide to
I saw an article that claimed Donald Trump recently tweeted 123 times in one day. This got me wondering how many times he typically tweets during a day, and whether this number has changed over the years. This seems like it might be a good topic to analyze with a
Recently I showed how to visualize and analyze longitudinal data in which subjects are measured at multiple time points. A very common situation is that the data are collected at two time points. For example, in medicine it is very common to measure some quantity (blood pressure, cholesterol, white-blood cell
This is a second article about analyzing longitudinal data, which features measurements that are repeatedly taken on subjects at several points in time. The previous article discusses a response-profile analysis, which uses an ANOVA method to determine differences between the means of an experimental group and a placebo group. The
Longitudinal data are used in many health-related studies in which individuals are measured at multiple points in time to monitor changes in a response variable, such as weight, cholesterol, or blood pressure. There are many excellent articles and books that describe the advantages of a mixed model for analyzing longitudinal
With time series data analysis, we can apply moving average methods to predict data points without seasonality. This includes Simple Average (SA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Exponential Moving Average (EMA), etc. For series with a trend but without seasonality, we can use linear, non-linear and autoregressive
What is an efficient way to evaluate a multivariate quadratic polynomial in p variables? The answer is to use matrix computations! A multivariate quadratic polynomial can be written as the sum of a purely quadratic term (degree 2), a purely linear term (degree 1), and a constant term (degree 0).
The English language can be a bit tough to learn. One reason is that sometimes words can have more than one meaning. For example, the word shady can mean "of doubtful honesty or legality," or it can mean "giving shade from sunlight." Which of those meanings am I thinking about,
My colleague, Mike Drutar, recently showed how to create a "strip plot" that shows the distribution of temperatures for each calendar month at a particular location. Mike created the strip plot in SAS Visual Analytics by using a point-and-click interface. This article shows how to create a similar graph by
Biplots are two-dimensional plots that help to visualize relationships in high dimensional data. A previous article discusses how to interpret biplots for continuous variables. The biplot projects observations and variables onto the span of the first two principal components. The observations are plotted as markers; the variables are plotted as
With all this sitting at a desk writing code, I have to do something to keep in shape. And for me, that something is paddling boats ... as fast as I can - and occasionally trying to race them. This past weekend I entered the race at Hunting Island, SC.
Understanding multivariate statistics requires mastery of high-dimensional geometry and concepts in linear algebra such as matrix factorizations, basis vectors, and linear subspaces. Graphs can help to summarize what a multivariate analysis is telling us about the data. This article looks at four graphs that are often part of a principal
Find out about the changes and enhancements to the best-selling book, The Little SAS Book.
After a marathon of a season, 162 games in each team's schedule to be precise, the stakes for Major League Baseball are higher in October, and postseason play is underway. Whether it's the renewal of an old rivalry, redemption for last year's runners up, or rooting for this season's breakout
Eliud Kipchoge recently ran a marathon in under 2 hours. It was a special marathon where they had set up the best possible conditions to help him achieve this goal (such as swapping in pace-setting runners to block the wind for him), so it won't count as the world record
In response to a recent article about how to compute the cosine similarity of observations, a reader asked whether it is practical (or even possible) to perform these types of computations on data sets that have many thousands of observations. The problem is that the cosine similarity matrix is an
Computing rates and proportions is a common task in data analysis. When you are computing several proportions, it is helpful to visualize how the rates vary among subgroups of the population. Examples of proportions that depend on subgroups include: Mortality rates for various types of cancers Incarceration rates by race
You've probably heard of the stupid 'challenges' where people usually end up hurting themselves (cinnamon challenge, Carolina reaper pepper challenge, etc). I thought it might be more helpful to society to have a challenge that could actually help people, rather than hurting them! Therefore I came up with the Halloween
The EFFECT statement is supported by more than a dozen SAS/STAT regression procedures. Among other things, it enables you to generate spline effects that you can use to fit nonlinear relationships in data. Recently there was a discussion on the SAS Support Communities about how to interpret the parameter estimates
The SAS Championship golf tournament is happening this week, here in Cary, North Carolina! If you're following along and watching the scores, you might wonder how they're doing compared to past years, and what kind of scores it generally takes to win. Follow along as I plot the data from
As a fellow student, I know that making sure you get the right books for learning a new skill can be tough. To get you started off right, I would like to share the top SAS books that professors are requesting for students learning SAS. With this inside sneak-peek, you
In a previous article, I mentioned that the VLINE statement in PROC SGPLOT is an easy way to graph the mean response at a set of discrete time points. I mentioned that you can choose three options for the length of the "error bars": the standard deviation of the data,
It is always great to read an old paper or blog post and think, "This task is so much easier in SAS 9.4!" I had that thought recently when I stumbled on a 2007 paper by Wei Cheng titled "Graphical Representation of Mean Measurement over Time." A substantial portion of
We've had record high 90+ degree temperatures here in the southeast US this past week (September / October), and it has made me appreciate having an air conditioner. Indeed, air conditioners were pretty much invented here in North Carolina (see Eric Cramer). They are used in pretty much every building
I frequently see questions on SAS discussion forums about how to compute the geometric mean and related quantities in SAS. Unfortunately, the answers to these questions are sometimes confusing or even wrong. In addition, some published papers and web sites that claim to show how to calculate the geometric mean
Lately we've been hearing a lot about "record low unemployment" in the news. Being a data guy, I wanted to see it for myself. Follow along as I create some custom unemployment graphs from the official data for California and New York (two of our most populous states). Or, if
In a scatter plot that displays many points, it can be important to visualize the density of the points. Scatter plots (indeed, all plots that show individual markers) can suffer from overplotting, which means that the graph does not indicate how many observations are at a specific (x, y) location.
A moving average is a statistical technique that is used to smooth a time series. My colleague, Cindy Wang, wrote an article about the Hull moving average (HMA), which is a time series smoother that is sometimes used as a technical indicator by stock market traders. Cindy showed how to
