 STA4321

Introduction to Probability

Dr. Yashowanto N. Ghosh (Visiting Professor)

08/2003 – 12/2003

Course Description:

Textbook: R.L. Scheaffer, Introduction to Probability and Its Applications, 2nd Edition,

The sequence of courses STA 4321–4322 (or STA 5325–5328) is designed to give student a formal and systematic introduction to mathematical statistics. Topics covered in STA 4321/5325 include basic formal probability elements, discrete and continuous variables, density functions, expectation and variance, conditional expectation, moment generating functions, multivariate random variables, distributions of functions of random variables, the law of large numbers and the central limit theorem.

My duty:

 STA4322

Introduction to Statistics Theory

Dr. Trevor Park

01/2004 – 05/2004

Course Description:

Textbook: An Introduction to Mathematical Statistics and its applications, by R. J.
Larsen and M. L. Marx, 4th Edition, 2006, Prentice Hall.

This is a direct continuation of STA 4321 (or STA 5325). It provides basic background material for distribution theory, estimation, and hypothesis testing, including comparison of two population parameters, and analysis of variance.

Sampling distributions, central limit theorem, estimation, properties of point estimators, confidence intervals, hypothesis testing, common large sample tests, normal theory small sample tests, uniformly most powerful and likelihood ratio tests, linear models and least squares, correlation. Introduction to analysis of variance.

My duty:

 STA6326

Introduction to Theoretical Statistics I

Dr. James Hobert

08/2004 – 12/2004

Course Description:

Textbook: 2nd edition of Statistical Inference by Casella and Berger

The sequence STA 6326-6327 introduces the fundamentals of the theory of mathematical statistics at the graduate level. In this course we will cover chapters 1-5 of the text: probability theory, transformations and expectations, common families of distributions, multiple random variables, and properties of a random sample. The prerequisite for the course is Analytic Geometry and Calculus 3 (MAC 2313).

Theory of probability. Probability spaces, continuous and discrete distributions, functions of random variables, multivariate distributions, expectation, conditional expectation, central limit theorem, useful convergence results, sampling distributions, distributions of order statistics, empirical distribution function.

My duty:

Grading homeworks and teaching weekly help sessions.

 STA6934

Spatial Data Analysis

Dr. Mike Daniels

08/2004 – 12/2004

Course Description:

Textbook: Statistical Analysis of Spatial Point Patterns, 2nd edition, Peter Diggle, Arnold, 2003

The course will provide an introduction to methods for the analysis of spatial data and be taught in basically three parts: 1) Geostatistical methods, 2) methods for lattice data, 3) methods for spatial point patterns.

My duty:

Grading homeworks and exams, holding TA hours.

 STA6327

Introduction to Theoretical Statistics II

Dr. James Hobert

01/2005 – 05/2005

Course Description:

Textbook: 2nd edition of Statistical Inference by Casella and Berger

Estimation and hypothesis testing. Sufficiency, information, estimation, maximum likelihood, confidence intervals, uniformly most powerful tests, likelihood ratio tests, sequential testing, univariate normal inference, decision theory, analysis of categorical data.

My duty:

 IEOR E4307

Industrial Forecasting

Dr. Kosrow Dehand

09/2007 – 12/2007

Course Description:

Textbook: Business Forecasting, John E. Hanke, Dean W. Wichern, Eighth Edition

Statistical forecasting applied in Business.

My duty: