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- 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
