In basic terms, the difference is that qualitative research collects data in the form of language, and quantitative research collects data in the form of numbers.
For example, “How satisfied are you with your life on a scale of one to ten?” is quantitative.
And “How satisfied are you with your life?” is qualitative.
Qualitative data does not necessarily have to involve asking participants questions and recording the response – it could be a literature search, review of diary entries – anything that is linguistic in format.
- It enables more complex aspects of a persons experience to be studied
- Fewer restriction or assumptions are placed on the data to be collected. For example, if I measure depression by asking ten 1-7 scale questions, I can only collect data on these ten things I’m asking about
- Not everything can be quantified, or quantified easily, and an advantage of qualitative research is that it can investigate these things (for example, individual experiences)
- Individuals can be studied in more depth
- Because fewer assumptions are placed on the thing being studied it is great for exploratory research and hypothesis generation
- The participants are able to provide data in their own words and in their own way
- It is more difficult to determine the validity and reliability of linguistic data
- It is harder to determine the extent of influence that the researcher had over the results (e.g., through researcher bias). That is, there is more subjectivity involved in analysing the data.
- Note, this doesn’t mean the data is necessarily less valid or reliable, just that it’s harder to know this (with quantitative data, you can do validity test, confirmatory analyses, and other stuff).
- “Data overload” – open-ended questions can sometimes create lots of data, which can take along time to analyse!
- Transcription of recorded interviews can often take a lot of time and/or money
Some advantages of self-report measures include:
- You get the respondents views directly
- A good way to measure a participants perception of the thing you are measuring
- Sometimes it only makes sense to measure something by asking the participant about it (opinions, for instance)
- Observational and objective data are not always possible to obtain – for example, life-history studies
- They are quick and simple to administer in many cases (e.g., questionnaires), no complicated technology is required
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