Introduction:
The moments of a distribution are statistical measures that provide information about the shape, spread, and central tendency of the distribution. In this question, we are given the first four moments of a distribution about the value 2. We need to comment on the nature of the distribution based on this information.

The First Moment:
The first moment of a distribution is the mean. In this case, the first moment is 1. This means that the distribution is skewed to the left, as the mean is less than the value about which the moments are calculated.

The Second Moment:
The second moment of a distribution is the variance. In this case, the second moment is 2.5. A small variance indicates that the data points are tightly clustered around the mean.

The Third Moment:
The third moment of a distribution is the skewness. In this case, the third moment is 5.5. A positive skewness indicates that the distribution is skewed to the right, with a long tail on the right-hand side.

The Fourth Moment:
The fourth moment of a distribution is the kurtosis. In this case, the fourth moment is 16. A high kurtosis indicates that the distribution has a sharp peak and heavy tails.

Conclusion:
Based on the information provided, we can conclude that the distribution is skewed to the left, with a small variance and a high kurtosis. The distribution is also skewed to the right, with a long tail on the right-hand side. Overall, the distribution is not normal and may have outliers or extreme values that are affecting the shape of the distribution. Further analysis would be required to determine the exact nature of the distribution.