Quantitative Data Analysis Styles

I have come to realise that there seem to be two approaches when it comes to quantitative data analysis. On one hand you have your scientific style where you make a hypothesis before you analyse your data (and hopefully before you collect it too!) to see if the data collected supports the hypothesis. This seems like a straightforward path with a single goal in mind. On the other hand, you have an alternative, free style where you collect the data and run statistical tests to find significant patterns in the data. This approach sounds more flexible and wider. As useful as the scientific style is, it seems to me that I will benefit more for the time by going down the free style path as it seems more interesting an avenue to develop some deep quantitative research skills.

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2 thoughts on “Quantitative Data Analysis Styles

  1. Personally, I prefer a mix of the two. There is a reason you collected the data in the first place that becomes your main hypothesis, but if you see an interesting pattern then there should be flexibility to explore it.

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