## 14.381 Statistical Method in Economics, Fall 2006

##### Author(s)

Chernozhukov, Victor
Download14-381-fall-2006/contents/index.htm (36.40Kb)

##### Alternative title

Statistical Method in Economics

##### Terms of use

##### Metadata

Show full item record##### Abstract

This course is divided into two sections, Part I and Part II. Part I provides an introduction to statistical theory and can be found by visiting 14.381 Fall 2018. Part II, found here, prepares students for the remainder of the econometrics sequence. The emphasis of the course is to understand the basic principles of statistical theory. A brief review of probability will be given; however, this material is assumed knowledge. The course also covers basic regression analysis. Topics covered include probability, random samples, asymptotic methods, point estimation, evaluation of estimators, Cramer-Rao theorem, hypothesis tests, Neyman Pearson lemma, Likelihood Ratio test, interval estimation, best linear predictor, best linear approximation, conditional expectation function, building functional forms, regression algebra, Gauss-Markov optimality, finite-sample inference, consistency, asymptotic normality, heteroscedasticity, and autocorrelation.

##### Date issued

2006-12##### Other identifiers

14.381-Fall2006

##### Other identifiers

14.381

IMSCP-MD5-c7202078f4362cd786a2bcb8ef2fcb3e

##### Based on

##### Keywords

statistical theory, econometrics, regression analysis, probability, random samples, asymptotic methods, point estimation, evaluation of estimators, Cramer-Rao theorem, hypothesis tests, Neyman Pearson lemma, Likelihood Ratio test, interval estimation, best linear predictor, best linear approximation, conditional expectation function, building functional forms, regression algebra, Gauss-Markov optimality, finite-sample inference, consistency, asymptotic normality, heteroscedasticity, autocorrelation

##### Collections

The following license files are associated with this item: