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Correspondence Analysis.

This is the ultimate guide for correspondence analysis, visualization, and interpretation. Everything you need to know is here: from basic how tos to tips and tricks that will aid in interpretation to advanced concepts. Worked examples are shown in Displayr, R and Q.

Correspondence analysis is a popular data science technique. It turns large tables of data into relatively easy to read visualizations. Which makes it easier to find key insights in the data. Correspondence analysis is also commonly used by market researchers to create brand switching and positioning maps. Scatter plots are the most common way to visualize results. However, moon plots have the same conclusions, are often even easier to interpret.

correspondence analysis movements How to Interpret Correspondence Analysis Plots (It Probably Isn’t the Way You Think)
19 May 2017 | by Tim Bock

Correspondence analysis is a popular data science technique. It takes a large table, and turns it into a seemingly easy-to-read visualization. Unfortunately, it is not quite as easy to read as most people assume. In How…

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Easily Add Logos to a Correspondence Analysis Map in Q
17 May 2017 | by Tim Bock

You can take your correspondence analysis plots to the next level by including images. Better still, you don’t need to paste in the images after the analysis is complete – you can include them right…

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correspondence analysis Easily Add Images to a Correspondence Analysis Map in Displayr
17 May 2017 | by Tim Bock

You can take your correspondence analysis plots to the next level by including images. Better still, you don’t need to paste in the images after the analysis is complete – you can include them right…

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correspondence analysis Easily Add Images to a Correspondence Analysis Plot in R
17 May 2017 | by Tim Bock

You can take your correspondence analysis plots to the next level by including images. Better still, you don’t need to paste in the images after the analysis is complete – you can include them right…

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Correspondence Analysis Using Correspondence Analysis to Find Patterns in Tables
13 February 2017 | by Tim Bock

There are lots of great visualizations designed for analyzing big quantities of data. Heatmaps, for example, are super-popular. However, when I am in a rush, my “go to” approach to analyzing big tables is almost…

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