Select the outlier in the data set. 3, 69, 71, 74, 78, 84, 87, 89, 97 If the outlier were removed from the data set, would the mean increase or decrease? Choices: (A)increase (B)decrease

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Select the outlier in the data set. 3, 69, 71, 74, 78, 84, 87, 89, 97  If the outlier were removed from the data set, would the mean increase or decrease?   Choices: (A)increase (B)decrease

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Identify Outlier: Identify the outlier in the given data set. The data set is: 3, 69, 71, 74, 78, 84, 87, 89, 97 An outlier is a data point that is significantly different from the rest of the data. We can use the interquartile range (IQR) method to identify outliers.Calculate Quartiles: Calculate the quartiles (Q1, Q2, Q3) of the data set. To find the quartiles, we need to arrange the data in ascending order (which it already is) and then find the median (Q2), the lower quartile (Q1), and the upper quartile (Q3). The data set in ascending order is: 3, 69, 71, 74, 78, 84, 87, 89, 97 Since there are 9 data points, the median (Q2) is the middle value, which is 78.Find Quartile Boundaries: Find the lower quartile (Q1) and the upper quartile (Q3). The lower half of the data set (below the median) is: 3, 69, 71, 74 The upper half of the data set (above the median) is: 84, 87, 89, 97 Since there are 4 numbers in each half, the lower quartile (Q1) is the average of the middle two numbers of the lower half: (69 + 71) / 2 = 70 The upper quartile (Q3) is the average of the middle two numbers of the upper half: (87 + 89) / 2 = 88Calculate IQR: Calculate the interquartile range (IQR). IQR = Q3 - Q1 = 88 - 70 = 18Determine Outlier Boundaries: Determine the outlier boundaries. The lower boundary for outliers is Q1 - 1.5 * IQR = 70 - 1.5 * 18 = 70 - 27 = 43 The upper boundary for outliers is Q3 + 1.5 * IQR = 88 + 1.5 * 18 = 88 + 27 = 115 Any data point below 43 or above 115 is considered an outlier.Identify Outliers: Identify the outlier(s) in the data set. Looking at the data set, the number 3 is below the lower boundary of 43, so it is an outlier.Calculate Mean with Outlier: Calculate the mean of the data set with and without the outlier. First, calculate the mean with the outlier: Mean with outlier = (3 + 69 + 71 + 74 + 78 + 84 + 87 + 89 + 97) / 9 Mean with outlier = 642 / 9 Mean with outlier = 71.33 (rounded to two decimal places)Calculate Mean without Outlier: Now, calculate the mean without the outlier: Mean without outlier = (69 + 71 + 74 + 78 + 84 + 87 + 89 + 97) / 8 Mean without outlier = 649 / 8 Mean without outlier = 81.13 (rounded to two decimal places)Determine Mean Change: Determine if the mean would increase or decrease upon removal of the outlier. Since the mean without the outlier (81.13) is greater than the mean with the outlier (71.33), the mean would increase if the outlier were removed.

Select the outlier in the data set. $\newline$ $3, 69, 71, 74, 78, 84, 87, 89, 97$ $\newline$ If the outlier were removed from the data set, would the mean increase or decrease? $\newline$ Choices: $\newline$ (A)increase $\newline$ (B)decrease

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Select the outlier in the data set.\newline3,69,71,74,78,84,87,89,973, 69, 71, 74, 78, 84, 87, 89, 973,69,71,74,78,84,87,89,97\newlineIf the outlier were removed from the data set, would the mean increase or decrease?\newlineChoices:\newline(A)increase\newline(B)decrease

Select the outlier in the data set. $\newline$ $3, 69, 71, 74, 78, 84, 87, 89, 97$ $\newline$ If the outlier were removed from the data set, would the mean increase or decrease? $\newline$ Choices: $\newline$ (A)increase $\newline$ (B)decrease