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Yes, it is.
Also normally distributed.
Yes, and more so for larger samples. (It follows from the Central Limit Theorem.)
The statement is true that a sampling distribution is a probability distribution for a statistic.
A sampling distribution refers to the distribution from which data relating to a population follows. Information about the sampling distribution plus other information about the population can be inferred by appropriate analysis of samples taken from a distribution.
Yes, it is.
Also normally distributed.
Yes, and more so for larger samples. (It follows from the Central Limit Theorem.)
A probability sampling method is any method of sampling that utilizes some form of random selection. See: http://www.socialresearchmethods.net/kb/sampprob.php The simple random sample is an assumption when the chi-square distribution is used as the sampling distribution of the calculated variance (s^2). The second assumption is that the particular variable is normally distributed. It may not be in the sample, but it is assumed that the variable is normally distributed in the population. For a very good discussion of the chi-square test, see: http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test
the standard deviation of the population(sigma)/square root of sampling mean(n)
The mean of the sampling distribution is the population mean.
The statement is true that a sampling distribution is a probability distribution for a statistic.
A sampling distribution refers to the distribution from which data relating to a population follows. Information about the sampling distribution plus other information about the population can be inferred by appropriate analysis of samples taken from a distribution.
The acronym CLT commonly stands for "Central Limit Theorem," a fundamental concept in statistics that states regardless of the shape of the population distribution, the sampling distribution of the sample mean will be approximately normally distributed for large sample sizes.
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.
welll its quiet simple to be honest 1st ASK YOUR TEACHER! that's what they are there for
As n increases the sampling distribution of pˆ (p hat) becomes approximately normal.