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← 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.