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6.2 Use Normal Distributions Pg. 219 Vocabulary • Normal Distribution – Modeled by a “bell-shaped” curve • Normal Curve – The “bell-shaped” curve is symmetric about the mean • Horizontal Reflection • Standard Normal Distribution – The normal distribution with a mean of 0 (zero) and a standard deviation of 1 (one). The formula below can be used to transform -values from a normal distribution with mean ( ) and standard deviation into z-values having a standard normal distribution z The Normal Distribution Empirical Rule: 68-95-99.7 • For a normal distribution, nearly all values lie within 3 standard deviations of the mean. • About 68% of the values lie within 1 standard deviation of the mean, 95% of the values lie within 2 standard deviations of the mean, and 99.7% of the values lie within 3 standard deviations of the mean. z - Score • The z–value for a particular –value (“mu” value) is called the z–score for the -value and is the number of standard deviations the – value lies above or below the mean . • To find the probability that z is less than or equal to some given value, we must use the table (pg 248) Example #1, Find a normal probability • A normal distribution has a mean of ( ) and a standard deviation ( ) . For a randomly selected –value from the distribution. – Find… P 3 P 3 0.34 0.135 0.023 0.4985 • We want the total probability that a randomly selected – value lies between and 3 Example #2 • Interpret normally distributed data – The heights of 3000 women at a particular college are normally distributed with a mean of 65 inches and a standard deviation of 2.5 inches. About how many of these women have heights between 62.5 inches and 67.5 inches? • First find where 62.5 and 67.5 are on the bell curve. – This area represents 68% on either side of the mean – So .68(3000)=2040 – 2040 women at this college have heights between 62.5 and 67.5 inches Example #3 • Find the probability that a randomly selected woman has a height of at most 68 inches. Homework Pg. 221 1 – 17 odd Pg. 222 1 – 19 odd