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Section 5.2 Normal Distributions: Finding Probabilities 1 Larson/Farber 4th ed

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Section 5.2 Objectives Find probabilities for normally distributed variables 2 Larson/Farber 4th ed

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Probability and Normal Distributions If a random variable x is normally distributed, you can find the probability that x will fall in a given interval by calculating the area under the normal curve for that interval. P(x < 600) = Area μ = 500 σ = 100 600μ =500 x 3 Larson/Farber 4th ed

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Probability and Normal Distributions P(x < 500) = P(z < 1) Normal Distribution 600μ =500 P(x < 600) μ = 500 σ = 100 x Standard Normal Distribution 1μ = 0 μ = 0 σ = 1 z P(z < 1) 4 Larson/Farber 4th ed Same Area

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Example: Finding Probabilities for Normal Distributions A survey indicates that people use their computers an average of 2.4 years before upgrading to a new machine. The standard deviation is 0.5 year. A computer owner is selected at random. Find the probability that he or she will use it for fewer than 2 years before upgrading. Assume that the variable x is normally distributed. 5 Larson/Farber 4th ed

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Solution: Finding Probabilities for Normal Distributions P(x < 2) = P(z < -0.80) = 0.2119 Normal Distribution 22.4 P(x < 2) μ = 2.4 σ = 0.5 x Standard Normal Distribution -0.80 0 μ = 0 σ = 1 z P(z < -0.80) 0.2119 6 Larson/Farber 4th ed

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Example: Finding Probabilities for Normal Distributions A survey indicates that for each trip to the supermarket, a shopper spends an average of 45 minutes with a standard deviation of 12 minutes in the store. The length of time spent in the store is normally distributed and is represented by the variable x. A shopper enters the store. Find the probability that the shopper will be in the store for between 24 and 54 minutes. 7 Larson/Farber 4th ed

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Solution: Finding Probabilities for Normal Distributions P(24 < x < 54) = P(-1.75 < z < 0.75) = 0.7734 – 0.0401 = 0.7333 2445 P(24 < x < 54) x Normal Distribution μ = 45 σ = 12 0.0401 54 -1.75 z Standard Normal Distribution μ = 0 σ = 1 0 P(-1.75 < z < 0.75) 0.75 0.7734 8 Larson/Farber 4th ed

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Example: Finding Probabilities for Normal Distributions Find the probability that the shopper will be in the store more than 39 minutes. (Recall μ = 45 minutes and σ = 12 minutes) 9 Larson/Farber 4th ed

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Solution: Finding Probabilities for Normal Distributions P(x > 39) = P(z > -0.50) = 1– 0.3085 = 0.6915 3945 P(x > 39) x Normal Distribution μ = 45 σ = 12 Standard Normal Distribution μ = 0 σ = 1 0.3085 0 P(z > -0.50) z -0.50 10 Larson/Farber 4th ed

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Example: Finding Probabilities for Normal Distributions If 200 shoppers enter the store, how many shoppers would you expect to be in the store more than 39 minutes? Solution: Recall P(x > 39) = 0.6915 200(0.6915) =138.3 (or about 138) shoppers 11 Larson/Farber 4th ed

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Are you here? Are you listening? The lengths of Altantic croaker fish are normally distributed with a mean of 10 inches and a standard deviation of 2 inches. A fish is randomly selected. If 500 croaker fish are caught, how many would you expect to be over 15 inches in length?

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Example: Assume that cholesterol levels of men in the United States are normally distributed, with a mean of 215 milligrams per deciliter and a standard deviation of 25 milligrams per deciliter. You randomly select a man from the United States. What is the probability that his cholesterol level is less than 175? Use a technology tool to find the probability. 13 Larson/Farber 4th ed

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Example: 175 – 215 = -1.6 25 P (x < 175) = P (z < -1.60) =.0548

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Section 5.2 Summary Found probabilities for normally distributed variables 15 Larson/Farber 4th ed

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5.1 Normal Probability Distributions Normal distribution A continuous probability distribution for a continuous random variable, x. The most important.

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