Bridging the Qual Quant Divide. Seriously.
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With the Information Deluge ( think IoT , Big Data, Engagement Economy…) , it does not require crystal ball gazing to determine that Qual and Quant approaches will need to cross-fertilise- with Quant learning to deal with fuzziness and context and Qual with huge sets of data and structure. Stands to reason that practitioners need to start understanding more...If you are a researcher , qual or quant but do not possess a sense of humour- do Not proceed ! The Qual/Quant divide has been a part of life as we know it and the stress involved in getting the twain to meet has prematurely greyed many managers !! …
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Editor's Notes
- If you are a researcher , qual or quant but do not possess a sense of humour- do Not proceed ! The Qual/Quant divide has been a part of life as we know it and the stress involved in getting the twain to meet has prematurely greyed many managers !!
- Quali perceives quant to be shovelling tons of data as throughput! Quant sees itself though as the steady ,solid Thinker!
- This is where self-view and others view of self possibly coincide!
- The Quant researcher sees the Qual as a diva holding forth ;The Quali sees self as hard-working ,have-to-do-everything-myself …
- Welllll, S.E. !
- Shades of grey vs. B&W
- Fuzzy Logic is good! As is Binary. There would be no computers without binary logic and there would be no decisions without fuzzy logic!
- Spartan Who?
- Probability is ,everything's Random nowadays!
- Quant researchers need a finite scale…how else would you compare mean scores?! Qual gets to be meaningfully different !
- Words are Qual fodder and the mode, the means to derive more meaning! I find Quant folk to be more mean minded!
- Self-explanatory ! The Quant researcher needs a ready structure whereas the Quali compatriot spins structure out of context!
- The Norm ! Said in hushed sepulchral tones …
- With the Information Deluge ( think IoT , Big Data, Engagement Economy…) , it does not require crystal ball gazing to determine that Qual and Quant approaches will need to cross-fertilise- with Quant learning to deal with fuzziness and context and Qual with huge sets of data and structure …