No, your telepathic powers are not sending me the correct image to be able to answer the question!
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
When the standard deviation of a population is known, the sampling distribution of the sample mean will be normally distributed, regardless of the shape of the population distribution, due to the Central Limit Theorem. The mean of this sampling distribution will be equal to the population mean, while the standard deviation (known as the standard error) will be the population standard deviation divided by the square root of the sample size. This allows for the construction of confidence intervals and hypothesis testing using z-scores.
normal distribution
The Central Limit THeorem say that the sampling distribution of .. is ... It would help if you read your question before posting it.
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.
welll its quiet simple to be honest 1st ASK YOUR TEACHER! that's what they are there for
It has the same shape, mean, and standard deviation as 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
Also normally distributed.
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.