Subject 'Mathematical Statistics'

Year:   2004/2005    2005/2006    2006/2007    2007/2008    2008/2009    

Overview of some Probability Distributions
Maximum Likelihood Estimators
Properties of Maximum Likelihood Estimators
Multivariate Normal Distribution and CLT
Confidence Intervals for Parameters of Normal Distribution
Gamma, Chi-squared, Student T and Fisher F Distributions
Testing Hypotheses about Parameters of Normal Distribution, t-Tests and F-Tests
Testing Simple Hypotheses
Bayes Decision Rules
Most Powerful Test for Two Simple Hypotheses
Chi-squared Goodness-of-fit Test
Chi-squared Goodness-of-fit Test for Composite Hypotheses
Tests of Independence and Homogeneity
Simple Linear Regression
Multiple Linear Regression
General Linear Constraints in Multiple Linear Regression
Analysis of Variance and Covariance

This course provides an elementary introduction to probability and statistics with applications.

Student should be able to use basic statistical models; distributions; statistical estimation and testing; confidence intervals; and linear regression.

This course features a full set of lecture notes, as well as assignments. Individual work - studying the given notes, solving exercises, preparing for tests and exam.

1. DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Boston, MA: Addison-Wesley, 2002.
2. Anderson D., Sweeney D., Williams T. Statistics for Busisness and Economics. West Publishing Company. 1996.
3. Lee C. F. Statistics for Business and Financial Economics. Lexington. 1993.

2008: MI*  

2007: MI*  

2006: MI*  

2005: MI*  

2004: MI*  TI*  

* Optional subject