Subject 'Statistical Analysis'

Year:   2015/2016    2016/2017    2017/2018    2018/2019    2019/2020    

Overview of some Probability Distributions
Maximum Likelihood Estimators
Properties of Maximum Likelihood Estimators
Multivariate Normal Distribution
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
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
Kolmogorov-Smirnov Test
Simple Linear Regression
Multiple Linear Regression
General Linear Constraints in Multiple Linear Regression

This course provides an elementary introduction to statistical analysis 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: LI  TI*  

2007: LI  TI*  

2006: LI  TI*  

2005: LI  RA*  TI*  

2004: LI  RA*  

* Optional subject