Yes, it is.
Also normally distributed.
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.
normal distribution
Yes, it is.
Also normally distributed.
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 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 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.
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.
normal distribution
normal distribution
The Central Limit THeorem say that the sampling distribution of .. is ... It would help if you read your question before posting it.
Sampling is needed in order to determine the properties of a distribution or a population. Sampling allows the scientist to determine the variance in an estimate.