 Bayesian experimental design is predicated on the belief that sound decisions and optimal utility can be made and achieved regarding a proposed experimental design despite uncertainty of the future and resource limitations as well as ethical constraints involving human subjects. The goal of experimental design in most circumstances is to maximize the probability of accruing accurate data within criterion such as financial, timing, geographic and cost considerations. It should also be noted that Bayesian techniques cannot only contribute to sound experimental design, but also affords statistical techniques that promote a Bayesian approach that emphasizes probabilities rather than frequencies to interpret and summarize data. This has proven to be particularly useful in experimental designs with small sample sizes. 