UCF QMB 3200 Final Exam Verified Questions with Correct Answers Graded A+

UCF QMB 3200 Final Exam Verified Questions with Correct Answers Graded A+ 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 Which of these best describes a sampling distribution of a statistic? It is the distribution of all of the statistics calculated from all possible samples of the same sample size. The probability distribution of all possible values of the sample proportion is the sampling distribution of p. For a fixed confidence level and population standard deviation, if we would like to cut our margin of error in half, we should take a sample size that is four times as large as the original sample size. We can reduce the margin of error in an interval estimate of p by doing any of the following except increasing the planning value p* to .5. When computing the sample size needed to estimate a proportion within a given margin of error for a specific confidence level, what planning value of p should be used when no estimate of p is available? 0.50 A statistics teacher started class one day by drawing the names of 10 students out of a hat and asked them to do as many pushups as they could. The 10 randomly selected students averaged 15 pushups per person with a standard deviation of 9 pushups. Suppose the distribution of the population of number of pushups that can be done is approximately normal. Which of the following statements is true? A t distribution should be used because σ is unknown. The z value for a 99% confidence interval estimation is 2.58 In an interval estimation for a proportion of a population, the critical value of z at 99% confidence is 2.576. In interval estimation, as the sample size becomes larger, the interval estimate becomes narrower.In general, higher confidence levels provide larger confidence intervals. One way to have high confidence and a small margin of error is to increase the sample size. From a population that is normally distributed, a sample of 30 elements is selected and the standard deviation of the sample is computed. For the interval estimation of μ, the proper distribution to use is the t distribution with 29 degrees of freedom. As the number of degrees of freedom for a t distribution increases, the difference between the t distribution and the standard normal distribution becomes smaller. The value added and subtracted from a point estimate in order to develop an interval estimate of the population parameter is known as the margin of error. What is the symbol for the population mean? If the population follows a normal distribution, the confidence interval is _____ and can be used for any sample size. If the population does not follow a normal distribution, the confidence interval will be _____. Which of the following choices correctly complete this statement? exact; approximate. The t value for a 99% confidence interval estimation based upon a sample of size 10 is 3.250. To compute the necessary sample size for an interval estimate of a population proportion, all of the following procedures are recommended when p is unknown except using .95 as an estimate. Using an α = .04, a confidence interval for a population proportion is determined to be .65 to .75. If the level of significance is decreased, the interval for the population proportion becomes wider. For a fixed confidence level and population standard deviation, if we would like to cut our margin of error to 1/3 of the original size, we should take a sample size that is nine times as large as the original sample size. The sampling distribution of can be approximated by a normal distribution as long as np 5 and n(1-p)5 greater or equals. When "s" is used to estimate "σ," the margin of error is computed by using the t distribution. The margin of error in an interval estimate of the population mean is a function of all of the following except the sample mean. For a fixed sample size, n, in order to have a higher degree of confidence, the margin of error and the width of the interval must be larger. The probability that the interval estimation procedure will generate an interval that does not contain µ is known as the level of significance. As the sample size increases, the margin of error decreases. When the level of confidence decreases, the margin of error becomes smaller. An approximate value of a population parameter that provides limits and believed to contain the value of the parameter is known as the interval estimate. To compute the necessary sample size for an interval estimate of a population mean, all of the following procedures are recommended when σ is unknown except using σ = 1. For the interval estimation of μ when σ is known and the sample is large, the proper distribution to use is the normal distribution. What is the symbol for the sample mean? X bar A student wants to determine if pennies are really fair, meaning equally likely to land heads up or tails up. He flips a random sample of 50 pennies and finds that 28 of them land heads up. What are the appropriate null and alternative hypotheses? H0: p=.5, Ha:p not =.5. For a lower tail test, the p-value is the probability of obtaining a value for the test statistic at least as small as that provided by the sample. The average hourly wage of computer programmers with 2 years of experience has been $21.80. Because of high demand for computer programmers, it is believed there has been a significant increase in the average wage of computer programmers. To test whether there has been an increase, the correct hypotheses to be tested are H0:u21.80, Ha: u21.80. In hypothesis testing, the tentative assumption about the population parameter is called the null hypothesis. For a two-tailed test, the p-value is the probability of obtaining a value for the test statistic as unlikely as that provided by the sample. The average number of hours for a random sample of mail order pharmacists from company A was 50.1 hours last year. It is believed that changes to medical insurance have led to a reduction in the average work week. To test the validity of this belief, the hypotheses are H0:u50.1, Ha:u50.1. Whenever the probability of making a Type II error has not been determined and controlled, only two conclusions are possible. We either reject H0 or Do not reject H0. Applications of hypothesis testing that only control for the Type I error are called significance tests. The p-value is a probability that measures the support (or lack of support) for the null hypothesis. As the test statistic becomes larger, the p-value becomes smaller. A news reporter states that the average number of temperature in January has never dropped below 10 degrees Fahrenheit. You go online to research this claim. The appropriate hypotheses are