Effect of sample size and method of sampling
pig weights on the accuracy of estimating the
mean weight of the population

Producers have adopted marketing strategies such as topping to help cut economic losses at the processing plant. Even though producers are implementing these strategies, they are still missing target weights and receiving substantial discounts. To assess this situation, we must first determine the accuracy of sampling methods producers use to estimate the mean weight of the population. The standard sampling procedure that has been adapted by many producers is to weigh a subsample of pigs in multiple pens (i.e., 5 pigs from 6 pens). Using a computer program developed in R (R Foundation for Statistical Computing, Vienna, Austria), we were able to generate 10,000 sample means for different sampling procedures on 3 different datasets. Using this program we evalu- ated taking: (1) a completely random sample of 10 to 200 pigs from the barn, (2) an increasing number of pigs per pen from 1 to 15 or the entire pen, and (3) increasing the number of pens until all pens had been sampled in the 3 separate datasets. This allowed us to provide tables for producers to decide on the sampling method and size necessary to achieve an acceptable estimation of pig weight in the barn. The analysis indicated that the number of pigs can be decreased by increasing the number of pens; however, the confidence interval (range in which 95% of weight estimates would fall) was still as high as 23 lb (242 to 265 lb) when only 30 pigs were sampled. Increasing the number of pens reduced the range between the upper and lower confidence interval, but not enough to make increasing pen sample size a practical means of estimating mean pig weight of the barn. Other methods of analysis must be designed to improve the accuracy of estimating pig mean weight in a facility other than random sampling of pigs within the barn.