Blog.
correspondence Analysis Visualization 5 ways to visualize relative importance scores from key driver analysis
26 April 2017 | by Tim Bock

Key driver analysis techniques, such as Shapley Value, Kruskal Analysis, and Relative Weights, are useful for working out the most important predictor variables for some outcome of interest (e.g., the drivers of satisfaction or NPS). But,…

Scatterplots A new R package for labeled scatterplots and bubble charts
26 April 2017 | by Tim Bock

  The rhtmlLabeledScatter package on github attempts to solve three chronic challenges with labeled scatterplots: readability with large numbers of labels, bubbles, and the use of images.   Four tools for dealing with overlapping labels 1….

Relative importance analysis table 4 reasons to compute importance using Relative Weights rather than Shapley Regression
19 April 2017 | by Justin Yap

Shapley regression is a popular method for estimating the importance of predictor variables in linear regression. This method can deal with highly correlated predictor variables that are frequently encountered in real-world data. Shapley regression has been gaining popularity…

Chart comparing Shapley with Relative Weights The difference between Shapley Regression and Relative Weights
19 April 2017 | by Justin Yap

Shapley regression and Relative Weights are two methods for estimating the importance of predictor variables in linear regression. Studies have shown that the two, despite being constructed in very different ways, provide surprisingly similar scores1Grömping, U. (2015). Variable importance in…

heatmap illusion Too hot to handle? The problem with heatmaps
13 April 2017 | by Tim Bock

Heatmaps are cool. Most people like them. They are so much prettier than a bar chart. The one below, created in Making your data hot: heatmaps for the display of large tables, is both nice to…

chartjunk The secret of “chartjunk”: Why misleading visualizations aren’t always bad
05 April 2017 | by Tim Bock

There is a war in the world of visualization. It is about chartjunk. Designers like to create charts like the one above. Many data viz experts think that such visualizations are appalling, calling the illustrations “chartjunk”….

The NPS recoding trick: the smart way to compute the Net Promoter Score
04 April 2017 | by Tim Bock

  The Net Promoter Score is most people’s go-to measure for evaluating companies, brands, and business units. However, the the standard way of computing the NPS – subtract the promoters from the detractors – is a bit of…

Assigning respondents to clusters/segments in new data files in Q
30 March 2017 | by Tim Bock

Once you have created segments or clusters, you may find it useful to assign people in other data sets to the segments (a process also known as segment tagging and scoring). For example, you may want to tag…

Assigning respondents to clusters/segments in new data files in Displayr
30 March 2017 | by Tim Bock

Once you have created segments or clusters, it is often useful to assign people in other data sets to the segments (this is also known as segment tagging and scoring). For example, you may want to tag a…

Custom sankey diagrams Creating custom Sankey diagrams using R
29 March 2017 | by Tim Bock

I have previously shown how Sankey diagrams can easily be used to visualize response patterns in surveys and to display decision trees. Following on from these posts, I will now be getting a bit more technical,…

Sankey diagram for analyzing survey routings, skips, filters, and response patterns Visualize response patterns and survey flow using Sankey Diagrams
29 March 2017 | by Tim Bock

If you have spent much time analyzing survey data, then you have probably spent a lot of time validating it. This normally entails checking that the number of people answering the different questions in a survey make sense. Where…

Heatmap Making your data hot: heatmaps for the display of large tables
22 March 2017 | by Tim Bock

  Sometimes tables are just too big to read. The table below shows the personality attributes that people associate with different iconic brands. A table too big to read easily and too big to show…