25. The mean monthly rent for a sample of studio apartments in one city is \( \$ 1100 \) with a standard deviation of \( \$ 210 \). The monthly rents for eight more studio apartments in the city a listed. Using the sample statistics above, determine which of the data values are unusual. Are any of the data values very unusual? Explain. (Assume the data set has a bell-shaped distribution.) \( \$ 1774, \$ 1536, \$ 1341, \$ 428, \$ 601, \$ 1062, \$ 947, \$ 796 \)
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To determine which of the data values are unusual, we can use the mean and standard deviation provided. Since the data is assumed to be normally distributed, we can identify unusual values as those that fall more than 2 standard deviations from the mean. The mean \(\mu\) is \$1100 and the standard deviation \(\sigma\) is \$210. Calculating the cutoff for unusual values: - Lower bound: \(\mu - 2\sigma = 1100 - 2(210) = 680\) - Upper bound: \(\mu + 2\sigma = 1100 + 2(210) = 1520\) Now, we can check the new apartment rent values against these boundaries: - \$1774 (greater than \$1520 - very unusual) - \$1536 (greater than \$1520 - very unusual) - \$1341 (within range - not unusual) - \$428 (less than \$680 - very unusual) - \$601 (less than \$680 - very unusual) - \$1062 (within range - not unusual) - \$947 (within range - not unusual) - \$796 (within range - not unusual) In summary, the rents of \$1774, \$1536, \$428, and \$601 are considered unusual, with the first two being very unusual due to being significantly above the average, while the latter two are very unusual for being well below the average. Remember, in statistics, unusual is just a fun way to say "outlier," and spotting these can help us understand the data better!