Probability weighting of data in small samples to facilitate nutritional interpretation

Food content or dietary intake is commonly calculated from very small numbers of estimates, and the distributions are often skewed. The mean value of a sample may not represent the health effect correctly, if the component or intake is skewed. A mean weighted towards the probability of more frequently occurring estimates should give a better indication of risk. Using 281 data values from a skewed food component distribution, ten random samples were created for each of 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50 and 100 randomly selected food component estimates per sample. The mean and a probability mean were calculated for each sample. The probability mean tended towards the population mean as the number of food components estimates per sample increased, but the two measures are different. It appears that using both the mean and the probability mean provides more information for the nutritional interpretation of data.