When errors are found, a common and standard assumption in practice is to assume Option A that the actual sample errors are representative of the population errors. Option B a 100% assumption for all errors. Option C that the population errors are larger than the sample errors. Option D that the population errors are smaller than the sample errors.
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Step 1: Identify the standard assumption in practice when errors are found: the sample errors are assumed to be representative of the population errors. Show more…
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Which of the following factors is not necessary in determining sample size? a. The standard deviation of the population. b. Magnitude of acceptable sampling error. c. The mean of the population. d. Confidence level. 2. Which of the following statements is incorrect about the sampling distribution of the sample mean? a. The mean of all possible sample means of size n is equal to the population mean. b. The standard error of the mean is equal to the standard deviation in the population divided by the square root of the sample size. c. The standard error of the sample mean will increase as the sample size increases. d. The sample mean is unbiased for the true population mean. 3. In hypothesis testing, the alternative hypothesis is a claim about a _________. a. population parameter that we are trying to find evidence for. b. sample statistic that will be true if the null hypothesis is false. c. population parameter that is assumed to be true until it is declared false. d. sample statistic that is assumed to be false until it is declared true.
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If you want to estimate a population proportion, with a sample of 400 cases, what will be the sampling error with a confidence level of 95%? Choose the right option: a) 5% b) 6.1% c) 4.9% d) Cannot be determined from given information. Which of the following relationships are valid with the sampling error? Explain your answer: a) The higher the population dispersion, the greater the sampling error. b) The greater the confidence in the estimate, the smaller the sampling error. c) The larger the sample size, the smaller the sampling error. d) The smaller the population dispersion, the greater the sampling error. e) The smaller the sample size, the smaller the sampling error. The sampling error refers to (choose the right option and explain): a) The natural variation existing between samples taken from the same population b) The use of non-probabilistic samples c) Systematic trends inherent in a sampling method that gives estimates of a parameter that are, on average, greater than the real parameter d) Human error in the sampling procedure.
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74. When the sample size is changed from 2500 to 900, what is the effect on the standard error? A. The new standard error is 9/25 times the old error. B. The new standard error is 3/5 of the old error. C. The new standard error is 5/3 of the old error. D. The correct answer is not among the choices. E. The new standard error is 25/9 of the old error. 67. The test statistic for a certain left-sided hypothesis test is zo = 0.40. At the 10% significance level, which of the following is false? A. The test is not statistically significant. B. P-value > significance level. C. The sample mean exceeds the mean stated in the null hypothesis. D. The correct answer is not among the choices. E. There is sufficient evidence to reject the null hypothesis. 68. Based on n = 25 observations, an appropriate 95% confidence interval for μ has been calculated as (-2.8, 2.42) from a population with a normal distribution. The hypotheses of interest are Ho: μ = 1 versus Ha: μ ≠ 1. Based on this confidence interval, which of the following is the best conclusion? A. We cannot perform the required test because we do not know the value of the test statistic. B. Reject Ho at the 0.05 level of significance, conclude that the mean is different from 1. C. We should not reject Ho at the 0.10 level of significance. D. Reject Ho at the 0.10 level of significance, conclude that the mean is different from 1. E. Do not reject Ho at the 0.05 level of significance, there is insufficient evidence that the mean is different from 1.
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