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the standard error will be 1

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Q: What is the distribution of sample means constructed by sampling 5 items from a population of 15?
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What is the number of samples for a distribution of sample means constructed by sampling 5 items from a population of 15?

the sampe mean cannot be comoputed


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

Population distribution refers to the patterns that a population creates as they spread within an area. A sampling distribution is a representative, random sample of that population.


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


When the population standard deviation is not known the sampling distribution is a?

If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.


What is the difference between population distribution and sample distribution an d sampling distribution?

you can figure it out by going to google and googling it


What is the purpose of a sampling distribution?

A statistic based on a sample is an estimate of some population characteristic. However, samples will differ and so the statistic - which is based on the sample - will take different values. The sampling distribution gives an indication of ho accurate the sample statistic is to its population counterpart.


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

12


When population distribution is right skewed is the sampling also with right skewed distribution?

If the population distribution is roughly normal, the sampling distribution should also show a roughly normal distribution regardless of whether it is a large or small sample size. If a population distribution shows skew (in this case skewed right), the Central Limit Theorem states that if the sample size is large enough, the sampling distribution should show little skew and should be roughly normal. However, if the sampling distribution is too small, the sampling distribution will likely also show skew and will not be normal. Although it is difficult to say for sure "how big must a sample size be to eliminate any population skew", the 15/40 rule gives a good idea of whether a sample size is big enough. If the population is skewed and you have fewer that 15 samples, you will likely also have a skewed sampling distribution. If the population is skewed and you have more that 40 samples, your sampling distribution will likely be roughly normal.


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 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?


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.


What is the meaning of Sampling distribution of the test statistic?

Given any sample size there are many samples of that size that can be drawn from the population. In the population is N and the sample size in n, then there are NCn, but remember that the population can be infinite. A test statistic is a value that is calculated from only the observations in a sample (no unknown parameters are estimated). The value of the test statistic will change from sample to sample. The sampling distribution of a test statistic is the probability distribution function for all the values that the test statistic can take across all possible samples.