{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Econ 210 Spring 2009 Problem Set 5 - Solutions

# Econ 210 Spring 2009 Problem Set 5 - Solutions - Econ 210...

This preview shows pages 1–2. Sign up to view the full content.

Econ 210 Spring Quarter 2009 Problem Set 5 - Solutions 1. True/False: a. The Central Limit Theorem ensures that an estimator is close to the true population value as the sample size gets large FALSE. That would be the LLN. b. An estimate is a random variable FALSE. An estimator is a random variable. Once you calculate, for example the sample mean, it is a constant number, not a random variable. c. If Y~(8,2) and N=1000 then P(Y>8)=0.5 FALSE. The random variable Y has an unknown probability distribution. This doesn’t change, even if we have an infinite number of sample observations. d. A biased estimator cannot be consistent FALSE. We showed that ( ) i X 2 is biased but consistent = = N i X X N s 1 2 1 ~ e. No estimator of the population mean has a lower variance than the sample mean FALSE. No LINEAR, UNBIASED estimator of the population mean has a lower variance than the sample mean. 2. What is the difference between unbiasedness and consistency?

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}