Recently a user posted a query on the SAS Communities page asking on how to create a histogram where the bins of the histogram are colored by the analysis variable using a three color ramp. Essentially, he wanted the bins to be colored from "Low" to "High" along the horizontal
Suppose you are creating a craft project for the Christmas holidays, and you want to choose a palette of Christmas colors to give it a cheery holiday appearance. You could use one of the many online collections of color palettes to choose a Christmas-themed palette. However, I didn't want to
The SGPLOT procedure enables you to use the value of a response variable to color markers or areas in a graph. For example, you can use the COLORRESPONSE= option to define a variable whose values will be used to color markers in a scatter plot or cells in a heat
If you perform a weighted statistical analysis, it can be useful to produce a statistical graph that also incorporates the weights. This article shows how to construct and interpret a weighted histogram in SAS. How to construct a weighted histogram Before constructing a weighted histogram, let's review the construction of
You can use histograms to visualize the distribution of data. A comparative histogram enables you to compare two or more distributions, which usually represent subpopulations in the data. Common subpopulations include males versus females or a control group versus an experimental group. There are two common ways to construct a
Recently Sanjay Matange blogged about how to color the bars of a histogram according to a gradient color ramp. Using the fact that bar charts and histograms look similar, he showed how to use PROC SGPLOT in SAS to plot a bar chart in which each bar is colored according
Often there are questions from users on creating histogram using a Log X axis. One such question came up this weekend, where a user wanted a histogram of her data using log axis. Before we get into her specific case, let us first clarify what we may want to see
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
There are many ways to visualize the distribution of univariate data. A previous article presents an overview and shows how to use SAS to create histograms, kernel density estimates, box plots, and cumulative distribution plots. This article continues the visualization journey, with an emphasis on dot plots and heat maps.
A recent article describes the main features of simulation by using the Synthetic Minority Over-sampling Technique (SMOTE). SMOTE was created to oversample from a set of rare events prior to running a machine learning classification algorithm. However, at its heart, the SMOTE algorithm (Chawla et al., 2002) provides a way
After giving a talk about how to create effective statistical graphics in SAS, I was asked a question: "When do you suggest using the graph template language (GTL) to build graphs?" I replied that I turn to the GTL when I cannot create the graph I want by using PROC
A common task in statistics is to model data by using a parametric probability distribution, such as the normal, lognormal, beta, or gamma distributions. There are many ways to assess how well the model fits the data, including graphical methods such as a Q-Q plot and formal statistical tests such
In a previous article, I presented some of the most popular blog posts from The DO Loop in 2024. In general, popular articles deal with elementary topics that have broad appeal. However, I also write technical articles about advanced topics, which typically do not make it onto a Top 10
This article shows how to simulate data from a Poisson regression model, including how to account for an offset variable. If you are not familiar with how to run a Poisson regression in SAS, see the article "Poisson regression in SAS." A Poisson regression model is a specific type of
A previous article discusses a formula for a confidence interval for R-square in a linear regression model (Olkin and Finn (1995) "Correlations redux", Psychological Bulletin) The formula is useful for large data sets, but should be used with caution for small samples. At the end of the previous article, I
A SAS programmer wanted to visualize density estimate for some univariate data. The data had several groups, so he wanted to create a panel of density estimate, which you can easily do by using PROC SGPANEL in SAS. However, the programmer's boss wanted to see filled density estimates, such as
In statistical quality control, practitioners often estimate the variability of products that are being produced in a manufacturing plant. It is important to estimate the variability as soon as possible, which means trying to obtain an estimate from a small sample. Samples of size five or less are not uncommon
These are a few of my favorite things. —Maria in The Sound of Music For my annual Christmas-themed post, I decided to forgo fractal Christmas trees and animated greeting cards and instead present a compilation of some of my favorite data visualization tips for advanced SAS users. Hopefully, this
A previous article defines the silhouette statistic (Rousseeuw, 1987) and shows how to use it to identify observations in a cluster analysis that are potentially misclassified. The article provides many graphs, including the silhouette plot, which is a bar chart or histogram that displays the distribution of the silhouette statistic
Assigning observations into clusters can be challenging. One challenge is deciding how many clusters are in the data. Another is identifying which observations are potentially misclassified because they are on the boundary between two different clusters. Ralph Abbey's 2019 paper ("How to Evaluate Different Clustering Results") is a good way
I recently blogged about how to compute the area of the convex hull of a set of planar points. This article discusses the expected value of the area of the convex hull for n random uniform points in the unit square. The article introduces an exact formula (due to Buchta,
SAS' Hamza Ghadyali reveals how to build computer vision solutions with privacy baked into their design.
SAS' Courtney Ambrozic highlights how to use SAS VDMML to assess lesion response to chemotherapy for patients with colorectal liver cancer.
While discussing how to compute convex hulls in SAS with a colleague, we wondered how the size of the convex hull compares to the size of the sample. For most distributions of points, I claimed that the size of the convex hull is much less than the size of the
SAS' Cindy Wang uses SAS Visual Analytics to explore how people around the world spend their days.
The number of possible bootstrap samples for a sample of size N is big. Really big. Recall that the bootstrap method is a powerful way to analyze the variation in a statistic. To implement the standard bootstrap method, you generate B random bootstrap samples. A bootstrap sample is a sample
You can use the bootstrap method to estimate confidence intervals. Unlike formulas, which assume that the data are drawn from a specified distribution (usually the normal distribution), the bootstrap method does not assume a distribution for the data. There are many articles about how to use SAS to bootstrap statistics
Many cities have Open Data pages. But once you download the data, what can you do with it? This is my second blog post where I download several datasets from Cary, NC's open data page, and and give you a few ideas to get you started on your own data
This article shows how to estimate and visualize a two-dimensional cumulative distribution function (CDF) in SAS. SAS has built-in support for this computation. Although the bivariate CDF is not used as much as the univariate CDF, the bivariate version is still a useful tool in understanding the probable values of
For many univariate statistics (mean, median, standard deviation, etc.), the order of the data is unimportant. If you sort univariate data, the mean and standard deviation do not change. However, you cannot sort an individual variable (independently) if you want to preserve its relationship with other variables. This statement is
