# What is the conjugate prior distribution? [duplicate]

I am new to the bayesian statistics and I most frequently see the conjugate prior distribution. Can you explain it with clear example? I would be very thankful.

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$$p(\theta|x) = \frac{p(x|\theta)p(\theta)}{\int{p(x|\theta)p(\theta)d\theta}}$$
The prior $$p(\theta)$$ is conjugate to the posterior $$p(\theta | x)$$ if both are in the same family of distributions.