If the data either underestimates or overestimates the true mean, incorrect assumptions regarding the population can be made which can influence selection decisions. The other noticeable difference in these two curves is the difference in variation. The curve representing the estimated data has a much smaller range with most data points clustered closely around the mean. The data has underestimated the true variation, suggesting that only small performance differences separate average and superior animals. However, the true case indicates a different scenario.
Larger differences do separate the average and superior animals.
Since the estimated data does not reflect the true scale, a larger percentage of animals that are near average, and less desirable for that trait would potentially be selected as parents. This causes genetic improvement to be less than what is possible. Another important aspect of data collection is that methodology and equipment used should provide repeatable results. This implies that repeated estimates taken on the same animal will be the same or nearly so. For instance, single animal weigh scales usually are rated for repeatability or precision.