Use the following to answer questions 26-33:The sampling distribution shows sample means from samples of size n = 50.What does one dot on the sampling distribution represent?Group of answer choicesThe mean of the quantity being estimated in one sample of 50 people.One person in the sampling distributionOne person in one sample of 50 people.The proportion of quantity being estimated in one sample of 50 people.None of the other answers are correct.

A distribution of a single statistic from repeated random samples of the same size from the same population refers to which of the following?Group of answer choicesDistribution of summary statisticsRandom samplingDistribution of population parametersThe normal curveSampling distribution of a statistic

In the simulation, when we are building a sampling distribution, what does each dot represent in the graph?An individual part-time college studentA random sample of 25 part-time college studentsA specific college’s part-time college studentsReset this ActivityDid I Get ThisIn the simulation, we collected thousands of random samples from a population of part-time college students. 60% of this population is female. What is the mean of the sample proportions?

he s.d. of the sampling distribution of sample mean for the population with s.d. 0.5, population size 122  and sample size 22 is*0.5/11None of these5/225/(11√22)

Suppose we take repeated random samples of size 20 from a population with a mean of 60 and a standard deviation of 8. Which of the following statements is true about the sampling distribution of the sample mean (x̄)? Check all that apply. The distribution is normal regardless of the shape of the population distribution, because the sample size is large enough. The distribution will be normal as long as the population distribution is normal. The distribution's mean is the same as the population mean 60. The distribution's standard deviation is larger than the population standard deviation of 8.

The sampling distribution of the sample proportion is the distribution of values of the sample proportion from all possible samples of size n drawn from a population. When a sample proportion is calculated, the population from which the sample comes is discrete. The variance of the sample proportion is equal to the variance of a binomial random variable divided by the sample size squared. The sampling distribution of the sample proportion is approximately normally distributed provided the population is normally distributed.