Almost any set of data that a law firm wants to analyze has some values missing. Missing values cause problems because many statistical or analytic algorithms drop all of the data for an observation that has even a single number missing. So, if you are studying your firm’s fees charged for reviewing securities law filings and you have completed 65 such matters over the past few years, if 10 of them are missing a number for total fees, you actually have an analyzable set of only 55 matters.
One choice would be to drop the matters that have a missing data point. But leaving out matters can result in a debilitating loss of other information on those matters, such as number of timekeepers, duration, etc. To counter this problem, analysts employ a range of methods to plug in plausible numbers for missing numbers and thereby save the remaining data. These methods are called “imputation,” and imputation is an important step when you prepare data for analysis. This article explains various methods of imputation, starting with the simplest and ending with sophisticated methods.
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