The difference between quantitative and qualitative research
Forever there seems to be a debate about the two and I am gob smacked by having a discussion with a positivist who seemed to think there is but one scientific method. So here's a provocation on how different the realities might be.
Here's one consideration of global warming demonstrated through the use of people's lived experiences as data as well as a visual ethnographic provocation to thoughtfulness.
It's an idiosyncratic representation.
http://www.flickr.com/photos/philsberry/2484326291/
In contrast here's how it is represented by the more positivist quantitative researchers:
This article points to the multiple research centres and claims "all" show that the Global surface temperature increased by 0.74 ± 0.18 °C (1.33 ± 0.32 °F) during the 100 years ending in 2005. Most conspicuously, according to the latest IPCC report the global surface temperature will likely to rise a further 1.1 to 6.4 °C (2.0 to 11.5 °F) during the twenty-first century.
Whose data is then backed up by multiple references to all the scientists of numerous countries, where repeated data provides validation. See http://www.theglobalwarmingstatistics.org/the-global-warming-statistics
This cheeky little posting is not to be taken too seriously.
Global warming might be.
How data is presented is very much a function of the ontological politics at play with beliefs held that extend as fas as whether the use of 'I' and open acknowledgement of a situated researcher has a place in formal writing. Please, I would like to put an end to the positivist belief of claiming objectivity. The question studies and the method of study are saturated with bias.
There are differences in the approaches that allow for the answering of different questions.
Qualitative research deals fundamentally in qualities: in experiences. This type of research is interested in how things are experienced. A core consideration is that the researcher experiences are also involved in what was studied; the how of this through to what is written, how it is written, and what is and isn't written or disseminated. The experience of qualitative research is imbued with epistemologies of how knowledge is made and what counts as knowledge. Every person's experience is as valid as anothers, this severely restrains any claims for generalisations. Reflexivity is expected.
Quantitive research deals fundamentally in quantities; in number crunching, in statistics, and addressing big data that allows for a probability (p value) index to support claims made.
Through random sampling and attending to sample size a probability index generates a measure to assess the level of confidence one might have in the findings of the research and in whether it might then have findings generalised to elsewhere.
A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis.
A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis.
A core consideration is that this method presents data as objective. There is an assumption of the data as separate to the researcher and so is written of with the absence of 'I' statements.
Obviously the two with their different epistemologies are difficult to reconcile. None the less, many people do with a "mixed-methods" approach. The clashing of philosophical underpinnings being subsumed with the value supposed from answering a question or issue from both the small scale of local experience as well as from the larger picture.
This link takes you to a slideshare where I have considered an area of interest (adverse events in the health sector) and considered how it might be studied in regard to these research methods. The slideshare was developed for a class I was teaching in called Methods of Research enquiry for undergraduate students from a variety of disciplines in a Health Faculty. The students needed to undertake a project as a group where they investigate a topic, consider the gaps in the literature and propose 2 research development plans, one qualitative, one quantitative.
This does bring up a point. For some people, the first representation has much more impact (makes more sense) than the second. Imagine what the audiences would be for each. Can you imagine giving a presentation to the World Bank using the first graphic?
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