Pratyaydipta Rudra

Directed research culminating in the PhD thesis.Offered for variable credit, 1-10 credit hours, maximum of 30 credit hours.Prerequisite(s): Consent of advisory committee.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 5543.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 4043.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Directed research culminating in the PhD thesis.Offered for variable credit, 1-10 credit hours, maximum of 30 credit hours.Prerequisite(s): Consent of advisory committee.

Methods of research and supervised thesis or report.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.Prerequisite(s): Consent of advisory committee.

Analysis of variance, experimental designs pertaining to medical research, regression and data modeling, categorical techniques and the evaluation of diagnostic tests. No credit for students with credit in STAT 5023.Prerequisite(s): STAT 5013.

Published journal articles from statistics or related areas are discussed. Previously offered as STAT 6001.Offered for fixed credit, 1 credit hour, maximum of 2 credit hours.Prerequisite(s): Consent of instructor.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 5543.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 4043.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 4043.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Directed research culminating in the PhD thesis.Offered for variable credit, 1-10 credit hours, maximum of 30 credit hours.Prerequisite(s): Consent of advisory committee.

Introductory statistics course for graduate students. Descriptive statistics, basic probability, estimation, hypothesis testing, p-values, analysis of variance, multiple comparisons, correlation and linear regression, categorical data analysis. Prerequisite(s): Graduate standing and MATH 1513.

Creative component for Applied Masters in Statistics. Prerequisite(s): Consent of advisory committee.

Directed research culminating in the PhD thesis.Offered for variable credit, 1-10 credit hours, maximum of 30 credit hours.Prerequisite(s): Consent of advisory committee.

Special subjects in statistics.Offered for variable credit, 1-6 credit hours, maximum of 6 credit hours.Prerequisite(s): Consent of instructor.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 5543.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 4043.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 5543.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Directed research culminating in the PhD thesis.Offered for variable credit, 1-10 credit hours, maximum of 30 credit hours.Prerequisite(s): Consent of advisory committee.

Different types of convergence in probability theory, central limit theorem, consistency, large sample estimation and tests of hypotheses, concepts of asymptotic efficiency, nonparametric tests. Previously offered as STAT 5203.Prerequisite(s): STAT 5223 and STAT 6113.

Investigation of special problems in the theory and application of statistics using current techniques. Special studies for PhD level students.Offered for variable credit, 1-6 credit hours, maximum of 12 credit hours.Prerequisite(s): Consent of instructor.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 5543.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 4043.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Matrix algebra, simple linear regression, residual analysis techniques, multiple regression, dummy variables, interactions, model building, introduction to logistic regression. This course explains fundamentals of linear regression and provides an introduction to logistic regression. May not be used for degree credit with STAT 4043.Prerequisite(s): One of STAT 4013, STAT 4033, STAT 4053, STAT 5013 or equivalent.

Directed research culminating in the PhD thesis.Offered for variable credit, 1-10 credit hours, maximum of 30 credit hours.Prerequisite(s): Consent of advisory committee.