![]() Collect sets of data where a relationship is present.In other words, more people are in the water on hot days when shark attacks occur, and more people are buying ice cream. ![]() The two may be correlated, but ice cream does not cause shark attacks–the heat of the day does. The example often used is shark attacks and ice cream sales. If you are looking for a way to do a graphical analysis of discrete data, you might try attribute charts. I suppose you also *could* put discrete data that comes out like pass/fail as one of two bands, but it would depend on whether or not you got any useful information out of the data. For the discrete data, you’d have to put it into some kind of quantified band–like say 1-10 on a customer satisfaction score. You could use discrete data on one scatter plot axis and continuous data on the other. Continuous data lets you measure things deeply on an infinite set and is generally make use in scatter analysis. ( See notes on the different data types here.)ĭiscrete data is best at pass/ fail measurements. Scatter analysis generally makes use of continuous data. What Kind of Data Should You Use for Scatter Analysis?
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