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Abstract
This study presents a new distribution using bayesian approach. The bayesian approach, in inference, is usually carried out in, choosing a probability density that expresses our degrees of beliefs about parameter before we see any data, choosing a statistical model that reflects our beliefs, after observing data we update our beliefs and forms the posterior distribution by applying Bayes{u2019} law of conditional probabilities. Acceptance sampling plans are commonly used to determine the acceptability of a product. When the life of a product is an important quality characteristic, sampling plans to determine acceptability of products with respect to life are called life test sampling plans. The objective of sampling plan is to find the minimum sample size and acceptability constant whose operating characteristic (OC) curve meets the requirements of the producer{u2019}s and the consumer{u2019}s risks. The objective of this dissertation is to propose ASPs for the mixture gamma - exponential distribution that we will derivate. We will assume the attribute sampling plan to find the minimum sample size and acceptance number. Hence assume the producer`s risk and consumer`s risk to drive the sampling plan, using MATHCAD