Answer by Daeyoung Lim:

*Parameters *are the __unknown__ numbers that describe the **population.**

Because we do not know the parameters, we come up with appropriate **estimators** to carry out significance tests or construct confidence intervals.

An **estimator** is the function of the random variables [math]X_1, X_2, \ldots, X_n[/math]. So mathematically, it's expressed like this: [math]g(X_1, X_2, \ldots, X_n)[/math] where g is a function. For example, a sample mean, [math]\frac{\sum_{i=1}^{n} X_i}{n}[/math] is also an estimator for the population mean [math]\mu[/math]. The same explanation applies for sample variance and the population variance.

The parameter of interest is the parameter you want to test with an estimator.

What does parameter of interest mean in statistics?

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