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← Z-Score - Intro to Descriptive Statistics

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Showing Revision 4 created 05/25/2016 by Udacity Robot.

  1. However, we're not just concerned with how far values are from the mean, we're
  2. also concerned with whether or not they're below the mean or above the mean.
  3. When you standardize any score on the x-axis, we get the z score. We already
  4. called it z before. And we're always going to subtract the mean from the x
  5. value, and then divide by the standard deviation. So that way if we have a value
  6. less than the mean, we're going to get a negative z score. The z score is
  7. basically the number of standard deviations any value is away from the mean.
  8. Therefore, we can convert any value in a normal distribution to a z score. When
  9. we do this, we standardize the distribution. We can start with any normal
  10. distribution, and then standardize it. So let's again, refer back to our normal
  11. distribution. The mean is 190, this is the actual mean of Facebook friends I've
  12. looked at up, but let's pretend that this standard deviation is 36 like it was
  13. in our example were Andy and I were arguing our unpopularity. So using this
  14. information click the link that we share and tell us how many Facebook friends
  15. you have And then calculate your z score. Later we're going to, to analyze that
  16. data and see if we get a normal distribution. So we'll be able to tell if some z
  17. score values don't match up. Do your best when you calculate your z score
  18. because it's good practice, and we're going to use z scores the rest of the
  19. class. If you don't have Facebook just enter 0, but be careful. This does not
  20. mean that your z score is going to be 0. You'll have to calculate that and
  21. figure out what it is. And I will know if you didn't calculate it correctly.