From the course: SPSS: Data Visualizing and Data Wrangling

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Recoding with visual binning

Recoding with visual binning

From the course: SPSS: Data Visualizing and Data Wrangling

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Recoding with visual binning

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- [Instructor] There's a school of thought in statistical data analysis that says you should never lose information in your variables. Now, that may seem like an obvious thing, but what we're talking about here, for instance, is levels of measurement. If you have a variable that, for example, is measured at the ratio level, it gives you a fair amount of information. Tells you where the absolute zero is, how far apart the scores are, you can make ratios between them. That's all great. And in an ideal world, yes, you would want to keep all of that. But an even more important rule is to make your analysis interpretable and put them in a way that gives you insight. And sometimes, by switching from a higher level of measurement to a lower level of measurement, say for instance going from a scaled quantitative variable to intervals or categories, can't serve those purposes, it's an informed decision, something that you get to do as an analyst to help guide you towards the actionable…

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