Suppose that a random sample of eighteen recently sold houses in a certain city has a mean sales price of $275,000, with a standard deviation of $7000. Under the assumption that house prices are normally distributed, find a 95% confidence interval for the mean sales price of all houses in this community. Then find the lower limit and upper limit of the 95% confidence interval. Carry your intermediate computations to at least three decimal places. Round your answers to the nearest whole number. (If necessary, consult a list of formulas.)

Use the t-table or any statistical tool and report the t-score that you multiple by the standard error to form the margin of error for a 95% confidence interval for a mean with 5 observations.   a. 2.132   b. 2.776   c. 2.015   d. 2.571

We would like to create a confidence interval for the mean. Which of the following would produce the smallest margin of error? Select one: a.A 95% confidence level and a sample size of 150 subjects b. A 99% confidence level and a sample size of 600 subjects. c. A 99% confidence level and a sample size of 150 subjects. d.A 95% confidence level and a sample size of 600 subjects.

Suppose we wish to calculate a 90% confidence interval for the average amount spent on books by freshmen in their first year at a major university. The interval is to have a margin of error of $2. Assume that the amount spent on books by freshmen has a normal distribution with a standard deviation of $30. How many observations are required to achieve this margin of error?

A standardized exam's scores are normally distributed. In a recent year, the mean test score was 1458 and the standard deviation was 312. The test scores of four students selected at random are 1860, 1220, 2150, and 1340. Find the z-scores that correspond to each value and determine whether any of the values are unusual. The z-score for 1860 is (Round to two decimal plaes as needed.)

Determine if the following statements are true or false. a. Jane took a sample of n = 100 observations from a population with mean and standard deviation. Mike also took a sample of n = 200 observations from the same population. Then, Mike’s sample mean will be closer to the true population mean than Jane’s sample. b. Jane took a sample of n = 100 observations from a population with mean and standard deviation. Mike also took a sample of n = 200 observations from a population with mean and standard deviation 2. Then, the sample mean from Mike’s sample is more likely to be close to the true mean than the sample mean from Jane’s sample. That is, the probability that X is between 90% and 110% of mean is higher for Mike’s sample than for Jane’s sample.