To determine which dataset is less spread out, we can calculate the mean absolute deviation (MAD) for each dataset. The mean absolute deviation is calculated as follows:
- Find the mean of the dataset (which we know is 62 for both datasets).
- Calculate the absolute deviation of each value from the mean.
- Find the average of these absolute deviations.
Dataset #1: {51, 53, 56, 60, 72, 80}
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Mean = 62
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Absolute deviations:
- |51 - 62| = 11
- |53 - 62| = 9
- |56 - 62| = 6
- |60 - 62| = 2
- |72 - 62| = 10
- |80 - 62| = 18
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Sum of absolute deviations = 11 + 9 + 6 + 2 + 10 + 18 = 56
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Mean absolute deviation (MAD) for Dataset #1 = 56 / 6 ≈ 9.3
Dataset #2: {49, 55, 61, 63, 70, 74}
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Mean = 62
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Absolute deviations:
- |49 - 62| = 13
- |55 - 62| = 7
- |61 - 62| = 1
- |63 - 62| = 1
- |70 - 62| = 8
- |74 - 62| = 12
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Sum of absolute deviations = 13 + 7 + 1 + 1 + 8 + 12 = 42
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Mean absolute deviation (MAD) for Dataset #2 = 42 / 6 ≈ 7.0
Conclusion:
- MAD for Dataset #1 = 9.3
- MAD for Dataset #2 = 7.0
Since the mean absolute deviation of Dataset #2 (7.0) is less than that of Dataset #1 (9.3), Dataset #2 is less spread out.
The correct response is:
Dataset #2 is less spread out because it has a mean absolute deviation of 7 whereas Dataset #1 has a mean absolute deviation of approximately 9.3.