Using 47 seasons of Survivor data, this analysis explores what gameplay traits correlate with winning, applying Python and SAS Viya Workbench to build predictive models. While stats like challenge wins and voting accuracy help narrow down potential winners, the findings suggest that intangible social dynamics play the most decisive role.
SAS programmers love to brag that the SAS will still run a program they wrote twenty or forty years. This is both a blessing and a curse. It's a blessing because it frees the statistical programmer from needing to revisit and rewrite code that was written long ago. It's a
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 binomial regression model, the response variable is the proportion of successes for a given number of trials. In SAS regression procedures, you specify a binomial model by using the EVENTS/TRIALS syntax on the MODEL statement. Many analysts use the LOGISTIC or GENMOD procedures to fit binomial models. Visualizing
Many people have an intuitive feel for residuals in least square models and know that the sum of squared residuals is a goodness-of-fit measure. Generalized linear regression models use a different but related idea, called deviance residuals. What are deviance residuals, and how can you compute them? Deviance residuals (and
A previous article describes how to use SAS to find the inflection points of a 1-D function that you can evaluate at any point. The function must be given by a formula (or by an algorithm) because the root-finding algorithm needs to evaluate the function at arbitrary locations. However, sometimes
In 2024, I wrote about 80 articles for The DO Loop blog. My most popular articles were about SAS programming, data visualization, and statistics. If you missed any of these articles, here is the "Reader's Choice Awards" for some of the most popular articles from 2024! SAS Programming The following
In a correlation analysis, it is common to consider the correlations between all pairs of numerical variables. That is, if there are k numerical variables, most people examine the complete k x k matrix of correlations. This matrix is symmetric and has 1s on the diagonal, so more than half of the
When the SAS Global Forum 2020 conference was cancelled by the global COVID-19 pandemic, I felt sorry for the customers and colleagues who had spent months preparing their presentations. One presentation I especially wanted to attend was by Bucky Ransdell and Randy Tobias: "Introducing PROC SIMSYSTEM for Systematic Nonnormal Simulation".
A common way to visualize the sample correlations between many numeric variables is to display a heat map that shows the Pearson correlation for each pair of variables, as shown in the image to the right. The correlation is a number in the range [-1, 1], where -1 indicated perfect
In practice, there is no need to remember textbook formulas for the ANOVA test because all modern statistical software will perform the test for you. In SAS, the ANOVA procedure is designed to handle balanced designs (the same number of observations in each group) whereas the GLM procedure can handle
En un mercado con clientes cada vez más exigentes, la experiencia del cliente se ha convertido en un factor decisivo. En este contexto, la IA generativa emerge como un aliado estratégico, transformando la gestión de la experiencia del cliente y fortaleciendo la relación con ellos. Desde conversaciones automatizadas hasta la
Modern software for statistical graphics automatically handles many details and graph defaults, such as the range of the axes and the placement of tick marks. In the days of yore, these details required tedious manual calculations. Think about what is required to place ticks on a scatter plot. On the
In SAS, DATA step programmers use the IN operator to determine whether a value is contained in a set of target values. Did you know that there is a similar functionality in the SAS IML language? The ELEMENT function in the SAS IML language is similar to the IN operator
Isotonic regression (also called monotonic regression) is a type of regression model that assumes that the response variable is a monotonic function of the explanatory variable(s). The model can be nondecreasing or nonincreasing. Certain physical and biological processes can be analyzed by using an isotonic regression model. For example, a
One of the most exciting features of SAS Viya Workbench is that the code editor includes a generative AI component called SAS Viya Copilot. This feature was announced and demonstrated at SAS Innovate 2024. With the Copilot, you can specify a text prompt that generates SAS code. For example, you
This article discusses how to scale a probability density curve so that it fits appropriately on a histogram, as shown in the graph to the right. By definition, a probability density curve is scaled so that the area under the curve equals 1. However, a histogram might show counts or
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 analyst ran a linear regression model and obtained an R-square statistic for the fit. However, he wanted a confidence interval, so he posted a question to a discussion forum asking how to obtain a confidence interval for the R-square parameter. Someone suggested a formula from a textbook (Cohen,
A SAS analyst read my previous article about visualizing the predicted values for a regression model that uses spline effects. Because the original explanatory variable does not appear in the model, the analyst had several questions: How do you score the model on new data? The previous example has only
A SAS programmer was trying to implement an algorithm in PROC IML in SAS based on some R code he had seen on the internet. The R code used the rank() and order() functions. This led the programmer to ask, "What is the different between the rank and the order?
At a recent conference in Las Vegas, a presenter simulated the sum of two dice and used it to simulate the game of craps. I write a lot of simulations, so I'd like to discuss two related topics: How to simulate the sum of two dice in SAS. This is
Years ago, I wrote an article that showed how to visualize patterns of missing data. During a recent data visualization talk, I discussed the program, which used a small number of SAS IML statements. An audience member asked whether it is possible to construct the same visualization by using only
A SAS programmer wanted to estimate a proportion and a confidence interval (CI), but didn't know which SAS procedure to call. He knows a formula for the CI from an elementary statistics textbook. If x is the observed count of events in a random sample of size n, then the
The moment-ratio diagram is a tool that is useful when choosing a distribution that models a sample of univariate data. As I show in my book (Simulating Data with SAS, Wicklin, 2013), you first plot the skewness and kurtosis of the sample on the moment-ratio diagram to see what common
A dot plot is a standard statistical graphic that displays a statistic (often a mean) and the uncertainty of the statistic for one or more groups. Statisticians and data scientists use it in the analysis of group data. In late 2023, I started noticing headlines about "dot plots" in the
A statistical analyst used the GENMOD procedure in SAS to fit a linear regression model. He noticed that the table of parameter estimates has an extra row (labeled "Scale") that is not a regression coefficient. The "scale parameter" is not part of the parameter estimates table produced by PROC REG
With four parameters I can fit an elephant. With five I can make his trunk wiggle. — John von Neumann Ever since the dawn of statistics, researchers have searched for the Holy Grail of statistical modeling. Namely, a flexible distribution that can model any continuous univariate data. As the quote
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
This article looks at a geometric method for estimating the center of a multivariate point cloud. The method is known as convex-hull peeling. In two-dimensions, you can perform convex-hull peeling in SAS 9 by using the CVEXHULL function in SAS IML software. For higher dimensions, you can use the CONVEXHULL
