Which of the following best describes the sampling distribution of a statistic? a normal curve, for which probabilities are obtained by standardizing. a distribution of all parameters from the population that is to be randomly sampled. a distribution of a single statistic from repeated random samples of the same size, from the same population. a distribution of all possible summary statistics from a single random sample, from the same population. the mechanism that determines whether the random sampling was effective.

Step-by-step explanation:

We have to recall the central limit theorem for statistic distributions.

The central limit theorem states that as sample sizes grow large and samples are drawn at random from the population, the sample mean will follow a normal distribution with mean = mean of all sample means .

Thus here we are given 4 choices.

We find that

A distribution of a single statistic from repeated random samples of the same size, from the same population

is the right answer.

Because when we test mean or any single statistic from repeated samples from the same population, we get the normal curve.

the answer is 844

step-by-step explanation:

it is 844 because if you add 836.50 + 7.5 you will get 844

answer: list the statements and i will follow up!

step-by-step explanation: