From the course: Data Science Foundations: Data Assessment for Predictive Modeling
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Taking an initial look at possible key variables
From the course: Data Science Foundations: Data Assessment for Predictive Modeling
Taking an initial look at possible key variables
- [Instructor] Okay, let's take a look at a data set called Phone Service Customers. This is available in the Originals folder. And we're going to take a look at the data set and look for possible ID fields, simply any field that might help us merge this data with other data. So the obvious choice is phone customer. So hopefully we'll have other information that we can bring in with that but that certainly looks like it's what we need. But we have a bunch of other possibilities. For instance, street address might allow us to identify if we have multiple customers at the same address. And that could be very interesting indeed. Email address is an interesting one because we wouldn't assume that we have email address for everyone. So it could be that we have a different set of services for those individuals for whom we know their email address. For instance, we might have an email address for somebody that belongs to a loyalty…
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Contents
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Reviewing basic concepts in the level of measurement3m 15s
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What is dummy coding?2m 31s
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Expanding our definition of level of measurement5m 44s
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Taking an initial look at possible key variables2m 51s
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Dealing with duplicate IDs and transactional data3m 49s
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How many potential variables (columns) will I have?4m 53s
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How to deal with high-order multiple nominals2m 30s
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Challenge: Identifying the level of measurement1m 39s
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Solution: Identifying the level of measurement3m 59s
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