Every day we face risks. If we drive to work, we risk a fatal auto accident. If we eat red meat and fatty foods, we risk a heart attack. If we go out in public during a pandemic, we risk contracting a disease. A logical response to risk is to

## Tag: **Statistical Thinking**

During an outbreak of a disease, such as the coronavirus (COVID-19) pandemic, the media shows daily graphs that convey the spread of the disease. The following two graphs appear frequently: New cases for each day (or week). This information is usually shown as a histogram or needle plot. The graph

Books about statistics and machine learning often discuss the tradeoff between bias and variance for an estimator. These discussions are often motivated by a sophisticated predictive model such as a regression or a decision tree. But the basic idea can be seen in much simpler situations. This article presents a

The ROC curve is a graphical method that summarizes how well a binary classifier can discriminate between two populations, often called the "negative" population (individuals who do not have a disease or characteristic) and the "positive" population (individuals who do have it). As shown in a previous article, there is

The purpose of this article is to show how to use SAS to create a graph that illustrates a basic idea in a binary classification analysis, such as discriminant analysis and logistic regression. The graph, shown at right, shows two populations. Subjects in the "negative" population do not have some

In a previous article, I showed how to perform collinearity diagnostics in SAS by using the COLLIN option in the MODEL statement in PROC REG. For models that contain an intercept term, I noted that there has been considerable debate about whether the data vectors should be mean-centered prior to

In my book Simulating Data with SAS, I show how to use a graphical tool, called the moment-ratio diagram, to characterize and compare continuous probability distributions based on their skewness and kurtosis (Wicklin, 2013, Chapter 16). The idea behind the moment-ratio diagram is that skewness and kurtosis are essential for

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

In a linear regression model, the predicted values are on the same scale as the response variable. You can plot the observed and predicted responses to visualize how well the model agrees with the data, However, for generalized linear models, there is a potential source of confusion. Recall that a

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,