Provide unbiased estimator for known distribution and prove it is unbiased

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I am trying to solve an old exercise from a statistics exam but I don't know the subject well and I hit a wall. You are given the following distribution:

\begin{align*} f(x)=\frac{2g+1}{2g}x^\frac{1}{2g} \end{align*}

With $g$ positive and $0\le x\le 1$.

I've already found an estimator for $g$, however now I am asked to find an unbiased estimator for its mean $\mu$ and prove that it is unbiased. I don't know how to do that, at least not for this particular distribution. I already found the value of $\mu$ by integrating (I found it to be $(2g+1)/(4g+1)$), and I know I somehow have to prove that the average of the estimator is equal to μ but idk how to do that. Can anyone help?

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now I am asked to find an unbiased estimator for its mean $\mu$ and prove that it is unbiased.

The simply way to answer is this.

An unbiased estimator for the $\mu$, the mean of the population is the sample mean

$$\hat{\mu}=\bar{X}_n$$

To prove it is unbiased is very easy

$$\mathbb{E}[\frac{1}{n}\sum_i X_i]=\frac{1}{n}\sum_i \mathbb{E}[X_1]=\frac{1}{n}\cdot n \mu=\mu$$