i dont no the answer
in order to calculate the mean of the sample's mean and also to calculate the standard deviation of the sample's
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
i dont no the answer
in order to calculate the mean of the sample's mean and also to calculate the standard deviation of the sample's
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) 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 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.
You calculate the standard error using the data.
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.
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.
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
The Central Limit THeorem say that the sampling distribution of .. is ... It would help if you read your question before posting it.