For all the strides that data mining tools have made, using them well still requires hard work and critical thought. This article is one in a series where we’re reviewing what it takes to be successful with data mining, what the common pitfalls are, how to avoid or remedy problems, and how to interpret results. This time we adresses a real workhorse for data mining and analysis, the histogram. Among the histograms encountered most frequently in practice are the following: “money”, “count”, and “outlier”. We will look at each one of them in turn. Read the full article