To determine which dataset is more spread out, we need to calculate the mean absolute deviation (MAD) for each dataset.
Step 1: Calculate the Mean Absolute Deviation (MAD) for Dataset #1
Dataset #1: {5, 8, 9, 10, 12, 12, 14}
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Find the mean (already given as 10, confirming our calculations).
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Calculate the absolute deviations from the mean:
- |5 - 10| = 5
- |8 - 10| = 2
- |9 - 10| = 1
- |10 - 10| = 0
- |12 - 10| = 2
- |12 - 10| = 2
- |14 - 10| = 4
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Sum absolute deviations:
\[ 5 + 2 + 1 + 0 + 2 + 2 + 4 = 16 \]
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Calculate MAD:
\[ MAD = \frac{16}{7} \approx 2.3 \]
Step 2: Calculate the Mean Absolute Deviation (MAD) for Dataset #2
Dataset #2: {5, 6, 8, 9, 10, 10, 22}
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Find the mean (already given as 10).
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Calculate the absolute deviations from the mean:
- |5 - 10| = 5
- |6 - 10| = 4
- |8 - 10| = 2
- |9 - 10| = 1
- |10 - 10| = 0
- |10 - 10| = 0
- |22 - 10| = 12
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Sum absolute deviations:
\[ 5 + 4 + 2 + 1 + 0 + 0 + 12 = 24 \]
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Calculate MAD:
\[ MAD = \frac{24}{7} \approx 3.4 \]
Step 3: Compare the Results
- Dataset #1: MAD ≈ 2.3
- Dataset #2: MAD ≈ 3.4
Conclusion
Dataset #2 is more spread out because it has a mean absolute deviation of 3.4, while Dataset #1 has a mean absolute deviation of 2.3.
So, the final answer is: Dataset #2 is more spread out because it has a mean absolute deviation of 3.4 while Dataset #1 has a mean absolute deviation of 2.3.