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Select the outlier in the data set. \newline62,72,76,77,78,82,84,94,37762, 72, 76, 77, 78, 82, 84, 94, 377

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Q. Select the outlier in the data set. \newline62,72,76,77,78,82,84,94,37762, 72, 76, 77, 78, 82, 84, 94, 377
  1. Arrange Data Set: Arrange the data set in ascending order.\newlineData set in order: 62,72,76,77,78,82,84,94,37762, 72, 76, 77, 78, 82, 84, 94, 377.
  2. Calculate IQR: Calculate the interquartile range (IQR).\newlineFirst, find the medians of the lower and upper halves.\newlineLower half: 62,72,76,7762, 72, 76, 77; Median = (72+76)/2=74(72 + 76) / 2 = 74.\newlineUpper half: 82,84,94,37782, 84, 94, 377; Median = (84+94)/2=89(84 + 94) / 2 = 89.\newlineIQR = Upper median - Lower median = 8974=1589 - 74 = 15.
  3. Determine Outlier Threshold: Determine the outlier threshold.\newlineLower bound = Q11.5×IQR=741.5×15=51.5Q1 - 1.5 \times IQR = 74 - 1.5 \times 15 = 51.5.\newlineUpper bound = Q3+1.5×IQR=89+1.5×15=111.5Q3 + 1.5 \times IQR = 89 + 1.5 \times 15 = 111.5.
  4. Identify Outliers: Identify any numbers outside the outlier threshold. The number 377377 is way above the upper bound of 111.5111.5, making it an outlier.

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