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2017 UA Data User Meeting Presentations

Data 101

  • Designed for new users
  • Subsets of our best variables
  • Tailored for popular research topics

Data Cleaning

Data cleaning was the final step in the processing of the data. In general terms, cleaning involved the standardization of values, including:

Also important was the exclusion of values that did not fit the form or logical possible content of a particular variable, such as when a number had been input for a variable requiring an alphabetic value. Whenever possible, errors of this sort have been corrected by consulting the original records, a process that continues today. Some variables (such as residence and occupation) also have been subjected to a coding process, undertaken for the purposes of clarifying and simplifying the range of data values. Any coding of a variable will be described in detail in the codebooks, which contain the most intricate information about the variables in the data sets.