In this case, you could identify three or four relatively distinct clusters – as shown in this next chart. And, at times, you can cluster the data via visual means.Īs you can see in this scatter graph, each individual case (what I’m calling a consumer for this example) has been mapped, along with the average (mean) for all cases (the red circle).ĭepending upon how you view the data/graph – there appears to be a number of clusters. In this cluster analysis example we are using three variables – but if you have just two variables to cluster, then a scatter chart is an excellent way to start. Step Two – If just two variables, use a scatter graph on Excel Figure 2 ![]() ![]() You can see from this example set that three start positions have been highlighted – we will discuss those in Step Three below. It’s just easier for me to classify that person in the “over $250,000” income bracket and scale income 1-9 – but that’s up to you depending upon the data you are working with. Say, for example, I am using income data (a demographic measure) – most of the data might be around $40,000 to $100,000, but I have one person with an income of $5m. ![]() The reason for this is to “contain” any outliers. NOTE: I prefer to use scaled data – but it is not mandatory.
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