UCF QMB 3200 Final Exam Question and Answers latest 2024

UCF QMB 3200 FINAL EXAM QUESTION AND ANSWERS LATEST 2024 Doubling the size of the sample will reduce the standard error of the mean The sample mean is the point estimator of U A simple random sample of size n from an infinite population of size N is to be selected. Each possible sample should have the same probability of being selected Which of the following statements regarding the sampling distribution of sample means is incorrect? The standard deviation of the sampling distribution is the standard deviation of the population. A simple random sample of size n from an infinite population is a sample selected such that each element is selected independently and is selected from the same population The fact that the sampling distribution of sample means can be approximated by a normal probability distribution whenever the sample size becomes large is based on the central limit theorem. Cluster sampling is a probability sampling method. The central limit theorem states that if the sample size n is large, then the sampling distribution of the sample mean can be approximated by a normal distribution. The value of the _____ is used to estimate the value of the population parameter sample statistic The sampling distribution of is the probability distribution of all possible values of the sample proportion. Which of the following is not a symbol for a parameter? S. The sample statistic characteristic s is the point estimator of σ.. The distribution of values taken by a statistic in all possible samples of the same size from the same population is called a sampling distribution. Which of the following is a point estimator? S. As a rule of thumb, the sampling distribution of the sample proportion can be approximated by a normal probability distribution when n(1 - p) ≥ 5 and np ≥ 5. A sample of 92 observations is taken from an infinite population. The sampling distribution of is approximately normal because of the central limit theorem. The central limit theorem is important in Statistics because it enables reasonably accurate probabilities to be determined for events involving the sample average when the sample size is large regardless of the distribution of the variable. The distribution of values taken by a statistic in all possible samples of the same size from the same population is the sampling distribution of The sample