# Estimator

Still don’t quite understand the differences. Confidence Interval

### Estimates vs Estimators

Estimates: $θ,y ,μ $, etc → Calculated from samples Estimators: $θ~$ - a RV - $y_{i} $ came from $Y$ - estimator (like $θ~$)

### Biased vs. Unbiased Estimators

Originally heard this from David Silver’s RL course the notes David Silver’s RL course the notes Monte-Carlo Learning. Also wrote about these ideas in David Silver’s RL course the notes Monte-Carlo Learning. Also wrote about these ideas in Monte-Carlo Learning. Also wrote about these ideas in Bootstrapping and Sampling.

Learning again through STAT206.

I think when it is an unbiased estimator, then you have that $E(σ_{2})=σ_{2}$

This is the kind of proffs that they do in Research Papers, and actually we barely covered it in class, file:///Users/stevengong/My%20Drive/Waterloo/2A/STAT206/Final/STAT206/Exam%20Practice%20Full%20Solutions.pdf is a good example.

From Confidence Interval, we say that $S_{2}$ is an unbiased estimator of $σ_{2}$, but $σ_{2}$ is biased.