BAYESIAN STATISTICS AND IT'S APPLICATION IN QUALITY CONTROL

ABSTRACT

study introduces and applies Bayesian statistics in statistical quality control to determine the distribution of the probability that an item produced using a given production line or process is defective. The Markov Chain Monte Carlo (MCMC) was employed in this study for the estimation of the posterior distribution and for the simulation of the entire Bayesian modeling process. All analysis were performed with the use of R statistical software. Bayesian statistics which is a branch of statistics dealing with the application of Bayes’ theorem to statistical analysis, provides us with the mathematical tools to update our belief about random events in light of seeing new data or evidence about those events. Bayesian statistics can lead to very good close to accurate results as demonstrated in this study.