From the course: Data Science Foundations: Data Assessment for Predictive Modeling

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How to navigate borderline cases of variable type

How to navigate borderline cases of variable type

From the course: Data Science Foundations: Data Assessment for Predictive Modeling

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How to navigate borderline cases of variable type

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- [Instructor] Okay, we're in KNIME with the same dataset, and the same workflow. So now what we're going to talk about is variables that seem like they might be one level of measurement but where there's some benefit to call them another level of measurement. I'll illustrate with an example. We're going to use hours. So the way that we're supposed to look at hours is with a histogram. So I start to types that in. And there's an interactive histogram, which we can use. We'll hook that up and when we go in, we don't want final weight, we want hours-per-week. And we definitely want to display all rows. Click on OK. Execute and open views. Okay, so we can see a pattern here. We can see that the tallest bar up here appears to be 33 to 41. Although 25 to 33 is a pretty tall bar as well. The problem is we can't see who said exactly 40. And just instinctively, we know that exactly 40 is going to be a common choice.…

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