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Managing Your Research Data

Tips & tools to help you manage your research data with less stress

Tips

  • Based on your analytical plan, identify the criteria your data need to meet so that you can answer your questions.
    • For example, if you plan to use a one-sample t test for independent means, your data have to meet the following assumptions:
      • interval or ratio scale of measurement
      • random sampling from a defined population
      • samples or data sets are linked in the population through repeated measures, natural association, or matching
      • scores are normally distributed in the population; difference scores are normally distributed
  • Take snapshots of your data at these key points, at least. A snapshot is just a locked copy of your data files, saved to a backup storage location. These files should not be changed; they are for reference only.
    • raw data (before it is cleaned and processed)
    • your processed data (before it is analyzed)
    • the data used for your analysis, any analytical scripts or procedures used, and detailed notes about why data were selected for analysis or excluded
  • Before you can begin to analyze your data, the data have to be cleaned, processed, screened, and sometimes split into separate datasets. This process can be full of confusion and uncertainty, but you can reduce it through planning, good note-taking, and taking snapshots (sometimes called data locks) of your data at key points in the data collection, processing, and analyzing process.

Tools