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Also normally distributed.

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Q: What will the sampling distribution of the mean be if a population is normally distribution?
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What is the mean of the sampling distribution equal to?

The mean of the sampling distribution is the population mean.


A sample of 24 observations is taken from a population that has 150 elements The sampling distribution of the mean is?

A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of is


What is sampling distribution of the mean?

Thanks to the Central Limit Theorem, the sampling distribution of the mean is Gaussian (normal) whose mean is the population mean and whose standard deviation is the sample standard error.


The mean of a sampling distribution is equal to the mean of the underlying population?

This is the Central Limit Theorem.


We have a population with mean of 100 and standard deviation of 28 take repeated samples of size 49 and calculate the mean of each sample to form a sampling distribution Is it a Normal Distribution?

a) T or F The sampling distribution will be normal. Explain your answer. b) Find the mean and standard deviation of the sampling distribution. c) We pick one of our samples from the sampling distribution what is the probability that this sample has a mean that is greater than 109 ? Is this a usual or unusual event? these are the rest of the question.


The standard error of the mean is the standard deviation of the sampling distribution of the sample mean?

a large number of samples of size 50 were selected at random from a normal population with mean and variance.The mean and standard error of the sampling distribution of the sample mean were obtain 2500 and 4 respectivly.Find the mean and varince of the population?


When may the sampling distribution of x̅ be considered to be approximately normal?

the standard deviation of the population(sigma)/square root of sampling mean(n)


What do you mean by a statistic and its sampling distribution?

A statistic is a summary measure of some characteristic of a population. If you were to take repeated samples from the population you would not get the same statistic each time - it would vary. And the set of values you would get is its sampling distribution.


What is the difference between a probability distribution and sampling distribution?

A sampling distribution function is a probability distribution function. Wikipedia gives this definition: In statistics, a sampling distribution is the probability distribution, under repeated sampling of the population, of a given statistic (a numerical quantity calculated from the data values in a sample). I would add that the sampling distribution is the theoretical pdf that would ultimately result under infinite repeated sampling. A sample is a limited set of values drawn from a population. Suppose I take 5 numbers from a population whose values are described by a pdf, and calculate their average (mean value). Now if I did this many times (let's say a million times, close enough to infinity) , I would have a relative frequency plot of the mean value which will be very close to the theoretical sampling pdf.


Which of the following is true regarding the sampling distribution of the mean for a large sample size?

It has the same shape, mean, and standard deviation as the population.


What is the difference between population and sample distribution?

Sampling distribution is the probability distribution of a given sample statistic. For example, the sample mean. We could take many samples of size k and look at the mean of each of those. The means would form a distribution and that distribution has a mean, a variance and standard deviation. Now the population only has one mean, so we can't do this. Population distribution can refer to how some quality of the population is distributed among the population.


Suppose that a population that a population has mean equals 64 and standard deviation equals 18. A sample of size 36 is selected. What is the mean of the sampling distribution of means?

64.