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I love the formattable package, but I always struggle to remember its syntax. A quick Google search reveals that I’m not alone in this struggle.…

In recent posts we’ve discussed how you can reference source tables using R in Q to manipulate the statistics into a new custom table. In…

You can have a video playing on a page in Displayr, as it’s very simple to set up. The video needs to be hosted on…

Q has a terrific feature whereby it can automatically compare statistics against the previous period (of time). This is great for tracking scenarios, when you…

Missing values in a data set are “blank” values. They are normally associated with survey skips. Those who skip a variable/question receive a missing value. Missing…

If you’ve studied a bit of statistics or machine learning, there is a good chance you have come across logistic regression (aka binary logit). It…

Feature engineering refers to the process of manipulating predictor variables (features) with the goal of improving a predictive model. In this post I outline some of the…

When creating a predictive model, there are two types of predictors (features): numeric variables, such as height and weight, and categorical variables, such as occupation…

When building a predictive model, it is often practical to improve predictive performance by modifying the numeric variables in some way. In statistics, this is…

Logistic regression, also known as binary logit and binary logistic regression, is a particularly useful predictive modeling technique, beloved in both the machine learning and the statistics communities. It…

A correlation matrix is a table of correlation coefficients for a set of variables used to determine if a relationship exists between the variables. The…