The Distinctions Between Quantitative and Qualitative Data Can

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The distinctions between quantitative and qualitative data can perhaps appear to be a bit of a dull subject. Does it really matter? Don’t we just pick a method that answers our research questions and off we go? Well, yes and no. Entire careers have been fought over exactly these questions. What counts as data, or more specifically what counts as meaningful data? What's going to tell us something that’s worth us knowing? So, yes, we have choices, and in one sense those choices are inevitably going to entail some kind of compromise. There will always be strengths and weaknesses, opportunities and limitations, to different approaches. Different methods will generate different kinds of data. Quantitative data are concerned with numbers, well, with quantities. We’re taking large amounts of information, such as people’s responses to a host of personality tests, or attitude questionnaires and transforming it into numerical values so that these can quickly be compared across large samples of people, like the scores on the scales devised by Adorno and his colleagues in the authoritarian personality study. Qualitative data is a bit harder to describe. It might draw on interviews or rich details of observations or case studies. Or examine people’s talk, how they make sense of the world and, so on. It might try to capture people’s experiences, their feelings, the way meanings are built up in terms of their sense of self and the wider world. Qualitative data is rich in description and we can discover all sorts of things about the psychological world by exploring what people say and do in a holistic way, trying to hold on to the richness and depth of psychological life. But, of course, it's precisely that richness which makes it hard to make straightforward comparisons. With quantitative data we are able to give numerical values to behaviours and this makes it possible to
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