Q1. Sampling error can be defined as: A) the standard deviation of a sampling distribution of the sample means. B) rejecting the null hypothesis when it is true. C) the difference between a sample statistic and its corresponding population parameter.
Q2. The sampling distribution of a statistic is: A) always a standard normal distribution. B) the same as the probability distribution of the underlying population. C) the probability distribution consisting of all possible sample statistics computed from samples of the same size drawn from the same population.
Q3. A sample of five numbers drawn from a population is (5, 2, 4, 5, 4). Which of the following statements concerning this sample is most accurate? A) The mean of the sample is ∑X / (n − 1) = 5. B) The variance of the sample is: ∑(x1 − mean of the sample)2 / (n − 1) = 1.5. C) The sampling error of the sample is equal to the standard error of the sample.
Q4. An analyst wants to generate a simple random sample of 500 stocks from all 10,000 stocks traded on the New York Stock Exchange, the American Stock Exchange, and NASDAQ. Which of the following methods is least likely to generate a random sample? A) Assigning each stock a unique number and generating a number using a random number generator. Then selecting the stock with that number for the sample and repeating until there are 500 stocks in the sample. B) Using the 500 stocks in the S& 500. C) Listing all the stocks traded on all three exchanges in alphabetical order and selecting every 20th stock.
Q5. A simple random sample is a sample constructed so that: A) the sample size is random. B) each element of the population has the same probability of being selected as part of the sample. C) each element of the population is also an element of the sample.
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