From the course: Data Science Foundations: Data Assessment for Predictive Modeling
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Solution: Identifying the level of measurement
From the course: Data Science Foundations: Data Assessment for Predictive Modeling
Solution: Identifying the level of measurement
(upbeat music) - [Instructor] Okay, let's talk about the level of measurement of each of these columns. Obviously Passenger ID is going to be an ID field. Survived is clearly a binary. Now granted, it's missing for the test data, but for all intents and purposes, it's a binary so that special kind of nominal that we talked about. Passenger Class. It's got three categories, first, second, third. Order is important here. It is true to say that second is in between first and third, so definitely ordinal. Name field. Definitely not nominal. Can't possibly be nominal. The reason is is that there's as many names as there are IDs, so logically we really have to think of this as an ID field. Now granted, if you stripped away just the last name, you could make some kind of variable that you would consider a high order nominal that was family unit or something, but really this is just as much an ID field as ID is…
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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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