# Bayesian posterior and prior distribution question

Here is my question:

You want to find proportion x of phones from a given company is defective. You are sent a box of 10 samples, and you find that two are defective.

1. Compute the posterior distribution for x using a uniform prior distribution.

2.Some time later, you are sent a second batch of 10 phones from the same company, but a different model. You find that three examples are defective in this new batch. Compute the updated posterior distribution. (One the includes the estimate obtained from the first batch).

I am not sure how to calculate the exact value of the first question since I got a beta(3,8) on question1. Also, for question2, how can I use the posterior distribution(beta(3,8))in question 1 to update the new posterior question? (I am also not sure whether using binomial distribution or beta distribution for this question)Thanks.

• Why do you have a problem with question 1? Look at what it's asking from you. For question 2, think about what you want to use as a prior distribution to compute the posterior. Do you still want to use a uniform prior? Or do you want that prior to reflect knowledge you have gained in the past? May 8, 2017 at 20:28
• I want to use the knowledge gained from the first question, and for question1, is there any way to get a numerical value, apart from beta(3,8)? Thanks May 8, 2017 at 20:39