# Create bins for lognormal data for cluster analysis

I have a series of dollar amounts that are highly right skewed, but are roughly log-normal. I want to put this grouped dollar amount as a predictor variable into a latent class cluster analysis. In this case I'm not sure whether transforming into log-normal makes sense for a predictor variable, as opposed to just binning the raw, skewed data.

Raw distribution:

Log-normal distribution:

• Why bin at all? Clustering can use the raw values. Note that binning (or not) is a quite separate question from whether values would be better considered on a logarithmic scale. – Nick Cox Apr 4 '15 at 15:50
• In your third sentence, did you mean to say "transforming into normal" rather than "transforming into log-normal"? – Glen_b Jun 11 '15 at 23:35

Ultimately, I discovered that there is no "correct' answer for this. One issue I had w/ trying to create lognormal data was that I had numerous data points with 0. Obviously negative infinity doesn't bin very well, so i had to force those values into the first bin. I ended up using Jenks natural breaks on the raw data through R's prabclus package.