4 Visualizations For Your Customer Satisfaction Data

Customer satisfaction is a valuable customer feedback metric. Here are the four visualizations to find stories in your customer satisfaction data.

How to Dynamically Change a Question Based on a Control Box

Control boxes are a popular way for users to change things on a Displayr page. This post will show you how to use a control...

What is Driver Analysis?

Driver analysis, which is also known as key driver analysis, importance analysis, and relative importance analysis, quantifies the importance of a series of predictor variables...

How to Interpret Logistic Regression Coefficients

This post describes how to interpret the coefficients, also known as parameter estimates, from logistic regression (aka binary logit and binary logistic regression). It does...

8 Tips for Interpreting R-Squared

Hopefully, if you have landed on this post you have a basic idea of what the R-Squared statistic means. The R-Squared statistic is a number...

How to Filter a Dashboard Based on User Logins

You can restrict what people see on a Displayr dashboard based on their department, geographic region, or some other user characteristic. For example, you can...

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8 Tips for Interpreting R-Squared

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Using R to Extract Information From an Object in Displayr
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7 Alternatives to Word Clouds for Visualizing Long Lists of Data

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Automatically Update Dashboards in Displayr

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How t-SNE works and Dimensionality Reduction

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Analyzing Google Trends Data in R

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Singular Value Decomposition (SVD) Tutorial Using Examples in R

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Hopefully, if you have landed on this post you have a basic idea of what the R-Squared statistic means. The R-Squared statistic is a number...

How to Check an Experimental Design (MaxDiff, Choice Modeling)

In this post, I explain the basic process that I tend to follow when doing a rough-and-ready check of an experimental design. The last step,…

Correspondence Analysis of Square Tables

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Using Bubble Charts to Show Significant Relationships and Residuals in Correspondence Analysis

While correspondence analysis does a great job at highlighting relationships in large tables, a practical problem is that correspondence analysis only shows the strongest relationships, and sometimes…

Why Capability Trumps Character for Supporters of the US President

American supporters of Donald Trump believe that financial skills are more important in a president than decency and ethics, a new survey shows. Data science…

Machine Learning: Pruning Decision Trees

In machine learning and data mining, pruning is a technique associated with decision trees. Pruning reduces the size of decision trees by removing parts of...

Old-School Crosstabs: Obsolete Since 1990, but Still a Great Way to Waste Time and Reduce Quality

The table above is what I call an old-school crosstab. If you squint, and have seen one of these before, then you can probably read it. The basic…

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In this post I explore two different methods for computing the relative importance of predictors in regression: Johnson’s Relative Weights and Partial Least Squares (PLS) regression. Both techniques solve a problem with…

Using Partial Least Squares to Conduct Relative Importance Analysis in R

Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis...

The Problem with Using Multiple Linear Regression for Key Driver Analysis: a Case Study of the Cola Market

A key driver analysis investigates the relative importance of predictors against an outcome variable, such as brand preference. Many techniques have been developed for key…

Using Partial Least Squares to Conduct Relative Importance Analysis in Displayr

Partial Least Squares (PLS) is a popular method for relative importance analysis in fields where the data typically includes more predictors than observations. Relative importance analysis…