To determine which measure of variability (IQR or MAD) best describes the spread of the dataset, we need to understand the characteristics of the data.
IQR (Interquartile Range) measures the spread of the middle 50% of the data and is less affected by outliers. It is calculated as the difference between the first quartile (Q1) and the third quartile (Q3).
MAD (Mean Absolute Deviation) measures the average distance of each data point from the mean. It is more sensitive to the overall distribution of the data points.
For this dataset, it looks like the wages have a fairly uniform distribution without extreme outliers, which could affect the mean more significantly than the quartiles. In this case, the IQR will provide a good measure of variability by focusing on the central part of the distribution.
Given that the dataset is relatively consistent and not significantly skewed, choosing IQR might be more appropriate.
Therefore, in this case, 1 (IQR) would be the better choice.