These are pre-approved graduate elective courses, for MS and PhD Students only, that can be substituted for a project management graduate program elective. However, it should be noted that seats in these courses are only available when students in the department’s major have been accommodated.
For pre-approved electives for MEng Students please see MEng Pre-Approved List.
The below information is also available as a pdf.
BUSI 764 Business Law for Managers; (3) Grade Method: REG.
Prerequisite: permission of department. Credit will be granted for only one of the following: BMGT 793 or BUSI 764. Formerly BMGT 793. Survey of United States legal institutions and processes as well as substantive areas of the law that affect business. Examination of tort and contract law, the legal forms of business organization and legal liability and major regulatory laws that affect business. Non-majors should review their registration eligibility in the statement preceding the BUSI courses. (Spring)
BMGT 830 Operations Research: Linear Programming (3)
Prerequisites: MATH 240 or equivalent; or permission of department.
Concepts and applications of linear programming models, theoretical development of the simplex algorithm, and primal-dual problems and theory. (Fall)
BMGT 831 Operations Research: Extension of Linear Programming and Network Analysis (3)
Prerequisite: BMGT 830 or equivalent; or permission of department.
Concepts and applications of network and graph theory in linear and combinatorial models with emphasis on computational algorithms. (not sure still offered)
BMGT 834 Operations Research: Probabilistic Models (3)
Prerequisites: {MATH 241; and STAT 400 or equivalent} or permission of department. Theoretical foundations for the construction, optimization, and applications of probabilistic models. Queuing theory, inventory theory, Markov processes, renewal theory, and stochastic linear programming. (Spring)
STAT 600 Probability Theory I (3)
Prerequisite: STAT410. Probability space; distribution functions and densities; Poissson limit theoreom; de Moivre-Laplace theorem; measure-theoretic definition of expectation; classification of measures on R; convergence of random variables; Radon-Nikodym theorem;LP spaces; conditional probabilities; independence of events, sigma-algebras and random variables; Bayes’ theo rem; pi-systems and Dynkin systems; discrete Markov chains; random walks; gambler’s ruin problem; Markov chains on a general phase space; Borel-cantelli lemmas; Kolmogorov inequality; three series theorem; laws of large numbers.
STAT 601 Probability Theory II (3)
Prerequisite: STAT600. Weak convergence of measures; characteristic functions; Central Limit Theorem and local limit theorem; stable laws; Kolmogorov consistency theorem (without proof); conditional expectations and martingales; optimal stopping theorem; convergence of martingales; Brownian motion; Markov processes and families; stochastic integral and Ito formula.
STAT 650 Applied Stochastic Processes (3)
Prerequisite: STAT410; or students who have taken courses with comparable content may contact the department. Basic concepts of stochastic processes. Markov processes (discrete and continuous parameters), Random walks, Poisson processes, Birth and death processes. Renewal processes and basic limit theorems. Discrete time martingales, stopping times, optional sampling theorem. Applications from theories of stochastic epidemics, survival analysis and others.
SURV 615 Statistical Methods I (3)
Prerequisite: Must have completed a two course sequence in probability and statistics; or students who have taken courses with comparable content may contact the department. Restriction: Must be in Survey Methodology (Master’s) program; or permission of instructor.
First course in a two term sequence in applied statistical methods covering topics such as regression, analysis of variance, categorical data, and survival analysis.
SURV 616 Statistical Methods II (3)
Prerequisite: SURV615.
Builds on the introduction to linear models and data analysis provided in Statistical Methods I. Topics include analysis of longitudinal data and time series, categorical data analysis and contingency tables, logistic regression, log-linear models for counts, statistical methods in epidemiology, and introductory life testing.
SURV 623 Data Collection Methods in Survey Research (3)
Prerequisite: SURV400; or students who have taken courses with comparable content may contact the department.
Review of alternative data collection methods used in surveys, such as current advances in computer-assisted telephone interviewing (CATI), computer-assisted personal interviewing (CAPI), and other methods such as touchtone data entry (TDE) and voice recognition (VRE).
SURV 625 Applied Sampling (3)
Prerequisite: Must have completed a course in statistics approved by department.
Practical aspects of sample design. Topics include: probability sampling (including simple random, systematic, stratified, clustered, multistage and two-phase sampling methods), sampling with probabilities proportional to size, area sampling, telephone sampling, ratio estimation, sampling error estimation, frame problems, nonresponse, and cost factors.
SURV 626 Sampling (2)
Prerequisite: Permission of BSOS-Joint Program in Survey Methodology department; and must have completed an introductory graduate level statistics course covering material through OLS and logistic regression.
Practical aspects of sample design. The course will cover the main techniques used in sampling practice: simple random sampling, stratification, systematic selection, cluster sampling, multistage sampling, and probability proportional to size sampling. The course will also cover sampling frames, cost models, and sampling error (variance) estimation techniques.
SURV 630 Questionnaire Design and Evaluation (3)
Credit only granted for: SURV430 and SURV630.
The stages of questionnaire design; developmental interviewing, question writing, question evaluation, pretesting, and questionnaire ordering and formatting. Reviews of the literature on questionnaire construction, the experimental literature on question effects, and the psychological literature on information processing. Examination of the diverse challenges posed by self versus proxy reporting and special attention is paid to the relationship between mode of administration and questionnaire design.
SURV 632 Social and Cognitive Foundations of Survey Measurement (3)
Major sources of survey error-such as reporting errors and nonresponse bias-from the perspective of social and cognitive psychology and related disciplines. Topics: psychology of memory and its bearing on classical survey issues (e.g., underreporting and telescoping); models of language use and their implications for the interpretation and misinterpretation of survey questions; and studies of attitudes, attitude change, and their possible application to increasing response rates and improving the measurement of opinions. Theories and findings from the social and behavioral sciences will be explored.
Some students wish to take electives in the Public Affairs program. These links can be viewed to search for courses:
Master of Public Policy
http://www.publicpolicy.umd.edu/graduate/masters/masters-of-public-policy
Master of Public Management
http://www.publicpolicy.umd.edu/graduate/masters/master-of-public-management
Master of Public Administration
http://www.publicpolicy.umd.edu/graduate/masters/master-professional-studies-public-administration
RDEV 603 Introduction to Real Property Finance (3)
Restriction: Permission of the Department. Credit only granted for: RDEV688Z, RDEV689V, or RDEV603. Formerly: RDEV688Z and RDEV689V.
Introduction to Real Property Finance addresses how real estate value is established, the fundamental foundations of the time value of money, as well as more real estate specific applications of return on investment, net operating income, the components of a real estate sources and uses statement, sources of real estate equity and debt financing, commonly used debt ratios and equity returns in real estate, as well as concepts of sensitivity analysis and exit strategies.
This article was last updated on January 4, 2022.