A consistent estimator for the mean collapses on the true parameter μ as the sample size increases, converging to the true value as more data is collected. It consistently follows a normal distribution and its variance decreases to zero as the sample size becomes infinitely large, accurately estimating the population mean.

1. A consistent estimator for the mean
Answer
collapses on the true parameter
µ
as the variance increases.
collapses on the true parameter
µ
as the sample size increases.
consistently follows a normal distribution.
is impossible to obtain using real sample data.
Solution
collapses on the true parameter µ as the sample size increases. Consistency is
when a parameters variance converges to zero in probability when the sample size is infinite.