Mathematical Statistics for Applied Econometrics — Introduction to Statistics, Probability and Econometrics
- Lecture I: Definitions and Course Overview Overheads .
- Bierens, Herman J. Introduction to Mathematical and Statistical Foundations of Econometrics Cambridge, UK: Cambridge University Press, 2005. Netlibrary .
- Notes on Measure Theory .
- Lecture II: Basic Axioms of Probability Overheads .
- Lecture III: Down the Rabbit Hole — An Odessy into Advanced Mathematics Overheads .
- Lecture IV:: Integrals and the Lebesgue Measure Overheads ,
Random Variables and Probability Distributions
- Lecture V: Probability Theory and Measure Overheads.
- Gauss Code Code which generates a sequence of Random Numbers.
- Gauss Output Resulting matrix of random numbers.
- Lecture VI: Random Variables and Probability Distributions Overheads .
- Lecture VII:Distribution Functions for Random Variables Overheads .
- Lecture VIII: Derivation of the Normal Distribution Overheads .
- Lecture IX: An Applied Sabbatical Overheads .
Moments and Moment Generating Functions
- Lecture X: Mean and Higher Moments Overheads .
- Lecture XI: Moments of More than One Random Variable Overheads .
- Lecture XII: Moment Generating Functions Overheads .
Binomial and Normal Random Variables
- Lecture XIII: Binomial and Normal Random Variables Overheads .
- Lecture XIV: Normal Random Variables Overheads .
- Lecture XIII: Bivariate and Multivariate Normal Random Variables Overheads .
Test I - October 4
Large Sample and Asymptotic Theory
- Lecture XVI: Large Sample Theory Overheads
- Lecture XVII: Limits and the Law of Large Numbers Overheads
- Lecture XVIIb: Fourier, Sobolev, and Complex Analysis Overheads
- Lecture XVIII: Empirical Examples of the Central Limit Theorem Overheads
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