At a large publishing company, the mean age of proofreaders is 36.2 years and the standarddeviation is 3.7 years. Assume the variable is normally distributed. Round intermediate z-value calculations to twodecimal places and the final answers to at least four decimal places. If a random sample of 20 proofreaders is selected, find the probability that the mean age of the proofreaders in the sample will be between 33.5 and 35 years. Assume that the sample is taken from a large population and the correction factor can be ignored.\[ P(33.5 < \overline{X} < 35) = \boxed{\phantom{0}} \]

From the provided information, Mean (µ) = 36.2 Standard deviation (σ) = 3.7 X~N (36.2, 3.7) Sample…

Answered: If a random sample of 20 proofreaders…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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At a large publishing company, the mean age of proofreaders is 36.2 years and the standard deviation is 3.7 years. Assume the variable is normally distributed. Round intermediate z-value calculations to two decimal places and the final answers to at least four decimal places.

If a random sample of 20 proofreaders is selected, find the probability that the mean age of the proofreaders in the sample will be between 33.5 and 35 years. Assume that the sample is taken from a large population and the correction factor can be ignored.

\[ P(33.5 < \overline{X} < 35) = \boxed{\phantom{0}} \]

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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