Today in 1A (Monday for 2B and 3B), we reviewed from last time, and then looked at the NORMAL CURVE.
- A lot of data, when you plot a HISTOGRAM of it, looks like
- a hill with lots of values piled up close to the MEAN, and then
- less and less as you go off to the sides.
- Here are the basic notes for a normal curve:
- Then, we used a Z-TABLE to find the probability for a value to be less than -3, -2, -1, 0, 1, 2, and 3 for a NORMAL CURVE with MEAN = 0 and STANDARD DEVIATION = 1:
- Notes from 1A:
- Slightly changed notes from 2B and 3B (same information, just different format):
- We saw that the normal curve is SYMMETRIC, because P(z<-3)=P(z>3), P(z<-2)=P(z>2), and P(z<-1)=P(z>1).
- Next we used these answers to show the EMPIRICAL RULE for normal curves.
- A data set is called NORMAL if:
- it looks normal, and
- it follows the EMPIRICAL RULE:
- 68% of the data within +/- 1 standard deviation of the mean,
- 95% of the data within +/- 2 standard deviations of the mean, and
- 99% of the data within +/- 3 standard deviations of the mean.
- Finally, we used this EMPIRICAL RULE to check whether data was NORMAL. We did only the first set in class, but here are both for your reference:
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