To determine the average deviation for each dataset in the tables, we can follow these steps:
- Calculate the sum of the distances from the mean for each table.
- Divide by the number of data points.
Table 1:
- Distances from the mean: 2, 0, 2, 3, 5, 2, 0
- Sum of distances: \(2 + 0 + 2 + 3 + 5 + 2 + 0 = 14\)
- Number of data points: 7
- Average deviation for Table 1: \(\frac{14}{7} = 2\)
Table 2:
- Distances from the mean: 1, 1, 4, 1, 1, 2, 2
- Sum of distances: \(1 + 1 + 4 + 1 + 1 + 2 + 2 = 12\)
- Number of data points: 7
- Average deviation for Table 2: \(\frac{12}{7} \approx 1.71\)
Now, we compare the average deviations:
- Average deviation for Table 1 = 2
- Average deviation for Table 2 ≈ 1.71
Since 2 (Table 1) is greater than 1.71 (Table 2), we conclude that the first table has a larger average deviation.
Therefore, the correct response is:
The first table has a larger average deviation.