From the past experience, it is known that the math score of graduates of an engineering college approximately follows a normal distribution with a standard deviation sigma = 21 When trying to find a 95% confidence interval for the mean math score using the sample mean, What is the size of the sample required to ensure that the error does not exceed 0.5 ? 4. From the past experience, it is known that the math score of graduates of an engineeringcollege approximately follows a normal distribution with a standard deviation o=21. When tryingto find a 95% confidence interval for the mean math score using the sample mean,What is the size of the sample required to ensure that the error does not exceed 0.5 ?

Standard deviation σ=21Margin of error E=0.5C.I = 95% = 0.95

Answered: From the past experience, it is known…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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From the past experience, it is known that the math score of graduates of an engineering college approximately follows a normal distribution with a standard deviation sigma = 21 When trying to find a 95% confidence interval for the mean math score using the sample mean, What is the size of the sample required to ensure that the error does not exceed 0.5 ?

4. From the past experience, it is known that the math score of graduates of an engineering
college approximately follows a normal distribution with a standard deviation o=21. When trying
to find a 95% confidence interval for the mean math score using the sample mean,
What is the size of the sample required to ensure that the error does not exceed 0.5 ?

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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