Effect of sampling method on the accuracy and precision of estimating the mean pig weight of the population

Producers have adopted marketing strategies such as topping to help reduce economic losses from weight discounts at the processing plant. Despite adopting these strategies, producers are still missing target weights and incurring discounts. One contributing factor is the error of sampling methods that producers use to estimate the mean weight of the population to determine the optimal time to top pigs. The standard sample size that has been adopted by many producers is 30 pigs. Our objective was to determine the best method for selecting 30 pigs to improve the accuracy and precision of estimating the mean pig weight of the population. 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 evaluated taking: (1) a completely random sample of 30 pigs from the barn, (2) a varying number of pigs per pen to achieve a total sample size of 30 pigs, (3) selecting the heaviest and lightest pig (determined visually) from 15 pens and calculating the mean from those pigs, and (4) calculating the median of the selected pigs.