1. The Central Limit Theorem allows for a researcher to: a. estimate the sampling distribution of a sample statistic, but only if the researcher takes many samples of the same size from the same population. b. estimate the sampling distribution of a sample statistic using the results from one sample taken from the population of interest. c. observe the true, population-level values of the quantity being estimated. d. ensure that the study results are scientifically useful. 2. Which of the following is not a property of a theoretical sampling distribution? a. As the size of the samples the statistics in the sampling distribution are based on increases, the center of the sampling distribution gets closer to the true values of the quantity being estimated. b. As the size that each statistic in the sampling distribution comes from increases, the variation in the values in the sampling distribution decreases. c. The characteristics of the sampling distribution are known, and its variability can be estimated without having to repeat a study over and over again. d. The shape of the sampling distribution is approximately normal, regardless of the shape of the individual observations being summarized by each statistic in the sampling distribution. 3. The variability in a collection of sample statistics from larger sized samples will tend to be _________ than/as variability from smaller sizes samples from the same population. a. There is no way to predict how the variability of these two collections of sample statistics will compare. b. Smaller c. Larger d. Exactly the same 4. The theoretical sampling distribution of a sample statistic, such as a sample mean or a sample proportion, is the distribution is: a. the distribution of all individual sample values from all possible random samples of the same size form the same population. b. the distribution of the true values for the underlying population level quantity that is being estimated by the sample statistics. c. the distribution of all possible values of the sample statistic across all possible random samples of the same size n, taken from the same population.
1. The Central Limit Theorem allows for a researcher to:
a. estimate the sampling distribution of a sample statistic, but only if the researcher takes many samples of the same size from the same population.
b. estimate the sampling distribution of a sample statistic using the results from one sample taken from the population of interest.
c. observe the true, population-level values of the quantity being estimated.
d. ensure that the study results are scientifically useful.
2. Which of the following is not a property of a theoretical sampling distribution?
a. As the size of the samples the statistics in the sampling distribution are based on increases, the center of the sampling distribution gets closer to the true values of the quantity being estimated.
b. As the size that each statistic in the sampling distribution comes from increases, the variation in the values in the sampling distribution decreases.
c. The characteristics of the sampling distribution are known, and its variability can be estimated without having to repeat a study over and over again.
d. The shape of the sampling distribution is approximately normal, regardless of the shape of the individual observations being summarized by each statistic in the sampling distribution.
3. The variability in a collection of sample statistics from larger sized samples will tend to be _________ than/as variability from smaller sizes samples from the same population.
a. There is no way to predict how the variability of these two collections of sample statistics will compare.
b. Smaller
c. Larger
d. Exactly the same
4. The theoretical sampling distribution of a sample statistic, such as a sample mean or a sample proportion, is the distribution is:
a. the distribution of all individual sample values from all possible random samples of the same size form the same population.
b. the distribution of the true values for the underlying population level quantity that is being estimated by the sample statistics.
c. the distribution of all possible values of the sample statistic across all possible random samples of the same size n, taken from the same population.
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