Prior and Posterior Distributions

Hi. I have this problem.

Suppose that the time in minutes required to servce a customer at a certain shop has an **exponential distribution** expressed as $\displaystyle f(x;\theta)=\theta exp(-\theta x)$, $\displaystyle x \ge 0$, where the parameter $\displaystyle \theta$ is unknown. Suppose that the **prior distribution** **of gamma** with **mean** $\displaystyle 0.2$ and **standard deviation** $\displaystyle 0.1$. The average time of service for a random sample of $\displaystyle 20$ customers is obserced to be $\displaystyle 3.8 $ minutes.

a) Find an expression for the joint density of the individual customer service times $\displaystyle X_1, ... ,X_20$.

So, the answer is just $\displaystyle \Pi_{n=1}^{20}f(x_i;\theta_1, ... , \theta_20)$

b) Find an expression for the prior density of $\displaystyle \theta$.

I'm not quite sure. I worked out Gamma's k value is $\displaystyle 4$ and $\displaystyle \theta=0.05$, but I don't think there's anthing to do with that.

c) Determine the posterior distribution up to a constant of proportionality.

i don't know how to do this...

d) Hence deduce the posterior distribution of $\displaystyle \theta$.

e) Use the mean of this posterior to estmate $\displaystyle \theta$.