What does the Central Limit Theorem tell about the sample mean? If the sample size is large, the distribution of all individual observations should be normally distributed. If your sample size is large, the distribution of the sample mean should be normally distributed with the population mean as its center. The distribution of the sample mean is always perfectly normally distributed. your sample size is large, the distribution of the population mean should be normally distributed with the population mean as its center.

What does the Central Limit Theorem tell about the sample mean? If the sample size is large, the distribution of all individual observations should be normally distributed. If your sample size is large, the distribution of the sample mean should be normally distributed with the population mean as its center. The distribution of the sample mean is always perfectly normally distributed. your sample size is large, the distribution of the population mean should be normally distributed with the population mean as its center.

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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Tiffany is a manager who needs to fire the worst performing 3% of employees. At her organization, employee performance is a normally distributed variable. Tiffany should fire employees who have a performance score that correspond with a z-score less than or equal to _____
For data that is not normally distributed we can't use z-scores. However, there is an equation that works on any distribution. It's called Chebyshev's formula. The formula is p = 1 - 7.2 where p is the minimum percentage of scores that fall within k standard deviations on both sides of the mean. Use this formula to answer the following questions. a) If you have scores and you don't know if they are normally distributed, find the minimum percentage of scores that fall within 2.1 standard deviations on both sides of the mean? b) If you have scores that are normally distributed, find the percentage of scores that fall within 2.1 standard deviations on both sides of the mean? c) If you have scores and you don't know if they are normally distributed, how many standard deviations on both sides of the mean do we need to go to have 96 percent of the scores? Note: To answer part c you will need to solve the equation for k.
he Princeton Review, a company that tracks information about various colleges, reports that 30% of CofC students are out-of-state students. If we took many samples of CofC students, and for each sample calculate the proportion $\hat{p}$ of out-of-state students in that sample, what would be the center of this distribution?
Explain why this statement is true: Suppose you take large repeated samples of a variable X (which is uniformly distributed). The distribution of the sample means will also be uniform.
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What price do farmers get for their watermelon crops? In the third week of July, a random sample of 40 farming regions gave a sample mean of x = $6.88 per 100 pounds of watermelon. Assume that ? is known to be $1.92 per 100 pounds.
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As the sample size (n) increases, does the sampling distribution of the sample mean stay the same, look more and more like a uniform distribution, or become more tightly clustered around the population mean?
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