1. 6. Day I: Normal Distributions
By the end of class you will be able to explain properties of a normal distribution.

2. We already saw distributions for Discrete Variables
Variables have a finite # of values

3. Now: Continuous Variables
Can take on an infinite # of values
Examples???

4. Heights of Classmates
What type of distribution do you think would represent the heights of everyone in this room?
Draw a picture of what you think this distribution would look like.

5. What’s Not Normal??

6. Left-Skewed Distribution
Also called Negatively Skewed
Majority of data falls to right of mean
Mean, Median, Mode
What kind of data do you think could be represented with this distribution?

7. Right-Skewed Distribution
Also called Positively Skewed
Majority of data falls to the left of the mean
Mode, Median, Mean
What kind of data do you think could be represented by this type of distribution?

8. What’s Normal??

9. Symmetric Distributions
Data values are evenly distributed around the mean
What kind of data do you think could be represented by this distribution?

10. Properties of Normal Distribution:
Bell Shaped
Mean, Median and Mode are the same and located at the center
Curve is unimodal
Curve is symmetric about the mean
Curve is continuous
Curve never touches the x-axis, but it gets closer and closer to it

11. Properties of Normal Distribution (contd)
Total area under the curve = 1, or 100%
Area under curve follows empirical rule
(SAT Scores)

12. The Equation:

13. ND: Same mean, different standard deviations:

14. ND: Different means, same standard deviation:

15. ND: different means and standard deviations:

16. Relay Summarizer
Each person writes a different fact about normal distributions.
Once you have four facts completely written out raise your paper.