To find the Mean Absolute Deviation (MAD) of the dataset \(10, 2, 5, 6, 7, 3, 4\), follow these steps:
- Calculate the mean (average) of the dataset.
- Find the absolute deviation of each number from the mean.
- Calculate the average of those absolute deviations.
Step 1: Calculate the Mean
\[ \text{Mean} = \frac{(10 + 2 + 5 + 6 + 7 + 3 + 4)}{7} = \frac{37}{7} \approx 5.29 \]
Step 2: Find Absolute Deviations
Now, we'll find the absolute deviation of each value from the mean:
- \( |10 - 5.29| \approx 4.71 \)
- \( |2 - 5.29| \approx 3.29 \)
- \( |5 - 5.29| \approx 0.29 \)
- \( |6 - 5.29| \approx 0.71 \)
- \( |7 - 5.29| \approx 1.71 \)
- \( |3 - 5.29| \approx 2.29 \)
- \( |4 - 5.29| \approx 1.29 \)
Step 3: Calculate the Mean of Absolute Deviations
Now, add up all the absolute deviations:
\[ 4.71 + 3.29 + 0.29 + 0.71 + 1.71 + 2.29 + 1.29 \approx 14.29 \]
Now, divide by the number of data points:
\[ \text{MAD} = \frac{14.29}{7} \approx 2.04 \]
Conclusion
The Mean Absolute Deviation (MAD) of the dataset \(10, 2, 5, 6, 7, 3, 4\) is approximately \(2.04\).