This is the Central Limit Theorem.
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.
It is the sampling distribution of that variable.
A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of is
The sampling distribution for a statistic is the distribution of the statistic across all possible samples of that specific size which can be drawn from the population.
This is the Central Limit Theorem.
Also normally distributed.
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.
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.
A set of probabilities over the sampling distribution of the mean.
NO
i dont no the answer
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.
It is the sampling distribution of that variable.
It will be the same as the distribution of the random variable itself.
A sample of 24 observations is taken from a population that has 150 elements. The sampling distribution of is
The statement is true that a sampling distribution is a probability distribution for a statistic.