Operationalising The Data

  • Operationalising the data is about making information or data usable
    • Within the analysis (SPSS) and presentation (word processor) software
    • Within your written work
  • Using a predefined procedure (step-by-step)
  • For example, how do you transpose words into numbers
    • Calculate the word frequency
    • Calculate the frequency of word length
    • Categorise words by their meaning
    • And so on…
  • Modern day electronic questionnaires automatically convert the response to in a numeric value for the most part by:
    • Using a rating scale (Likert)
    • Representing words with number (female=0, male=1)
  • If you use a data collecting tool which returns data in the wrong format you will need to convert this data into a usable format
  • Operationalising the data within your written work simply means converting the data into a meaningful or understandable value
    • Comparing groups (or events) using a percentage value (or zScore) not the raw value
      • Using the raw value makes it hard for the reader to remember whereas a percentage give a feeling of success e.g. closer to 100%
      • Comparing raw scores which are not equal can leading to misunderstandings

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