Answer:
a. Normal
Step-by-step explanation:
Hello!
Let X₁, X₂, ..., Xₙ be random variables that constitute a random sample, then any function of type Ô = h that depends solely on the n random variables and does not contain any unknown parameters is called the estimator of parameter θ. When this function h (.) It is applied to the set of the n numerical values of the respective random variables, a numerical statistic value is generated that receives the estimator name of the parameter Ô.
The function h (.) It is a function of random variables, so it is also a random variable, as a consequence of this, the estimator Ô has probability distribution with E (Ô) and V (Ô).
Applied to the normal distribution, if you have a random sample of n random variables X₁, X₂, ..., Xₙ that have a normal distribution, the sample mean calculated from this sample will be a random variable with the same distribution as the original variables.
X~N(μ;δ²) ⇒ X[bar]~N(μ;δ²/n)
I hope it helps!
