Normal Distribution Ball Drop Normal Distributions A normal

Normal Distribution Ball Drop

Normal Distributions A normal distribution is modeled by a bell-shaped curve called a normal curve that is symmetric around the mean. Most of the data is around the middle of the curve tails MEAN Median Mode tails Characteristics of a Normal Distribution: -Bell Shaped – symmetric (left side is EXACT mirror of the right side) with the data more concentrated in the middle than in the tails -Mean, Median, and Mode are the same value

Examples of Normal Distribution Curves. They all have the same characteristics of a normal curve! The difference is that there standard deviations are NOT the same! Standard deviation – is a statistic that tells you how tightly all of the values of your data are clustered around the mean. When the values are pretty tightly bunched together the curve is steep and the standard deviation is SMALL. When the values are spread apart the bell curve is relativity flat and the standard deviation is LARGE.

The Bell Curve

Empirical Rule!!!

Finding a Normal Probability Reminder: Probability must be a number between 0 and 1 mean two standard deviations above the mean

Example #1 A: 0. 84 A: 0. 16 A: 0. 34

Examples #2 Given the mean is 25 and the standard deviation is 8, find the following probabilities. 1. P(x<25) 2. P(x<17) 3. P(x>33) 4. P(x<9)

Examples #3 Given the mean is 6 and the standard deviation is 2, find the following probabilities. 1. P(4<x<8) 2. P(x<6) 3. P(4<x<10) 4. P(x>8) 5. P(x<12)

HOMEWORK • P. 266 (1 -17 odd)