A population of values has a distribution with urandom sample of size n=235.6 and o 32.1. You Intend to draw a58.According to the Central Limit Theorem:(a) What is the mean of the distribution of sample means?(b) What is the standard deviation of the distribution of sample means?(Report answer accurate to 4 decimal place.)(c) In a random sample of n=58, what is the probability that its sample mean is more than 235.3?Round to three decimal places.(d) In a random sample of n3D58, what is the probability that its sample mean is less than 232.8? Giveyour answer to three decimal places.Submit Question

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Answered: A population of values has a…

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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S2. Assume that x₁,...,10 € R satisfy Σ₁ x₁ = 3 and Σ₁x² = 10. What is the sample standard deviation of x₁,...,x10?
Assume that adults have IQ scores that are normally distributed with a mean of m = 105 and a standard deviation s =15. Find the probability that a randomly selected adult has an IQ between 91 and 119. The probability that a randomly selected adult has an IQ between 91 and 119 is ____.
a. Given x P(x) 1 3 4 5 0.15 0.24 0.3 0.31 Find (i) Mean (ii) Standard Deviation b) Probability of snowing during the month of February in nyc is 0.63. What is the probability that it will snow 3 of the next 7 days during the month of February in nyc ?
This is for statistics and probability
Q10. Z-score If Z is standard normal variable use the table of standard normal probabilities to find and draw the diagram. a) P(z2.13)
A variable of a population has a mean of μ = 250 and a standard deviation of σ = 35. a. The sampling distribution of the sample mean for samples of size 49 is approximately normally distributed with mean b. For part (a) to be true, what assumption did you make about the distribution of the variable under consideration? O A. Normal distribution. O B. Uniform distribution. O C. No assumption was made. c. Is the statement in part (a) still true if the sample size is 16 instead of 49? Why or why not? O A. Yes, the sampling distribution of the sample mean is always normal. O B. No, the sampling distribution of the sample mean is never normal for sample size less than 30. and standard deviation O C. No. Because the distribution of the variable under consideration is not specified, a sample size of at least 30 is needed for part (a) to be true.
A population has a mean of 200 and a standard deviation of 90. Suppose a simple random sample of size 125 is selected and is used to estimate μ. Use z-table. a. What is the probability that the sample mean will be within 18 of the population mean (to 4 decimals)? b. What is the probability that the sample mean will be within 16 of the population mean (to 4 decimals)?
g The following table shows the number of people that have either 0, 1, 2 or 3 cars registered in their name, from a sample of 305 people. a) Complete the table. (Hint: You will need to find P(x)) Number of cars owned 66 97 55 X 0 1 2 3 (b Find the mean number of cars owned for this sample. Give your answer to at least 2 decimal places. (c Find the standard deviation of cars owned for this sample. Give your answer to at least 2 decimal places. Question Help:Written Example Submit Question C M acer
The Central Limit Theorem says that the standard deviation of the sampling distribution of the sample means is (A exactly equal to the standard deviation. (B close to the population mean if the sample size is small close to the population standard deviation if the sample size is large. equal to the population standard deviation divided by the square root of the sample D size.
A variable of a population has a mean of u 200 and a standard deviation of o = 42. a. The sampling distribution of the sample mean for samples of size 49 is approximately normally distributed with mean b. For part (a) to be true, what assumption did you make about the distribution of the variable under consideration? A. No assumption was made. B. Normal distribution. C. Uniform distribution. c. Is the statement in part (a) still true if the sample size is 16 instead of 49? Why or why not? A. No. Because the distribution of the variable under consideration is not specified, a sample size of at least 30 is needed for part (a) to be true. O B. Yes, the sampling distribution of the sample mean is always normal. and standard deviation C. No, the sampling distribution of the sample mean is never normal for sample size less than 30.
A large corporation employs 37525 individuals. The average income of all employees is $76294, with a standard deviation of $17726 and is skewed to the right. Consider this to be the population distribution. You are given a data set consisting of the incomes of 140 randomly selected employees. The population mean is μ=μ= The population standard deviation is σ=σ= The sample size is n=n= Since the sample size is relatively large, the Central Limit Theorem tells us that the sample averages should have a sampling distribution that is (skewed to the rightapproximately normal). The sampling distribution of the sample means is centered at the (populationsample) mean. The sampling distribution has a standard deviation of SD=σ√n=SD=σn= . Round to two decimal places.
A variable of a population has a mean of μ=100 and a standard deviation of σ=42 a. The sampling distribution of the sample mean for samples of size 49 is approximately normally distributed with mean ____ and standard deviation ____ b. For part (a) to be true, what assumption did you make about the distribution of the variable under consideration?A. Normal distribution.B. No assumption was made.C. Uniform distribution. c. Is the statement in part (a) still true if the sample size is 16 instead of 49? Why or why not?A. No, the sampling distribution of the sample mean is never normal for sample size less than 30.B. No. Because the distribution of the variable under consideration is not specified, a sample size of at least 30 is needed for part (a) to be true.C. Yes, the sampling distribution of the sample mean is always normal.

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