Researchers working in cropping systems often include an examination of potential income level and income risk associated with each system. In most cases, income risk is measured by standard deviation of the income distribution, assuming that the distribution of income is normal. Since the distribution of income is a composite of the yield and price distributions, the characterization of these latter distributions also contributes to income risk dimensions. Most yield distributions are estimated by using either annualized data from long-term experimental trails or aggregated yields for a specific region, published by official governmental sources. In this research, the impact of source yield distribution selection on income risk is examined. Specifically, we characterize potato yield data from three sources: 1) average annual yields from long-term field studies; 2) individual field plot data to construct a “grand” yield distribution over the life of the long-term study; and 3) annual historical yields published by NASS. Our results show that mean yield, standard deviation and measures of skewness varied significantly between the various constructions of yield distributions. When combined with product price, the measures of income risk also depended on source yield distribution and showed significant differences. These findings illustrate the need for researchers to carefully assess the sources of their data when attempting to identify the economic impact with respect to income and income variability of cropping trials. This is especially important in projecting the trial results to the individual farm level.