## ← Different Data Types 1 - Numeric Data - Intro to Data Science

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Showing Revision 6 created 05/25/2016 by Udacity Robot.

1. So we've talked about visual cues to encode and represent
2. your data. Another thing we consider is the different types
3. of data that are available. Most data can be categorized
4. into 3 basic types. In fact, we've seen all 3
5. types of this data during our walk through of the
6. baseball data without explicitly referring to them as such. The
7. first of these types is numeric data. Numeric data as
8. you might expect, is any data where our data points
9. are exact numbers. These data have meaning as
10. a measurement such as a baseball player's height
11. or weight or as a count, such as number of hits or home runs for a player
12. or how many players there are on a
13. team. Statisticians also might call numerical data, quantitative data.
14. Numerical data can be characterized into discrete or
15. continuous data. Discrete data has distinct values whereas continuous
16. data can assume any value within a range. For
17. example, a player's number of home runs would be
18. a discrete data set. You can only have discrete
19. whole number values like 10, 25, or 34. A
20. player cannot for example, hit 14.375 home runs. A
21. player either hits a home run or he doesn't.
22. On the other hand, continuous data are numbers that
23. can fall anywhere within a range. Like a player's
24. batting average which falls between 0 and 1000. So
25. a player could have a batting average of 0.250, they
26. could also have a batting average of 0.357 or
27. 0.511. And so again just to hammer this home, examples
28. of numeric data might be a baseball player's height
29. or weight or their number of home runs or a
30. number of hits or a number of doubles. The
31. take away here is that this is data that are
32. numbers and they are not ordered in
33. time. They're just numbers that we've collected.