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2017-2018 Graduate Catalog 
    
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2017-2018 Graduate Catalog [ARCHIVED CATALOG]

Course Descriptions

 

Statistics
  

  • STAT 611 - Mathematical Statistics I

    [3]
    Random variables and their distribution functions, probability density and frequency functions, mathematical expectations and moments, moment-generating functions, characteristic functions, probability inequalities, special discrete and continuous distributions, multi-variate random vectors and their distributions, conditional and marginal distributions, conditional expectation, transformation and functions of random variables, modes of convergence and central limit theorem.
    Prerequisite: Prerequisite: STAT 451 or consent of instructor. Credit will not be given for both STAT 611 and STAT 651 .
  

  • STAT 612 - Mathematical Statistics II

    [3]
    Sampling distribution, estimation and testing of statistical hypotheses, principles of estimation, unbiasedness, minimum variance, consistency, Rao-Cramer inequity, Rao-Blackwell theorem, sufficiency, multi-parameter estimation, maximum likelihood and moment estimates, the Neyman-Pearson approach, UMP test, unbiased and consistent tests and multi-parameter hypotheses.
    Prerequisite: Prerequisite: STAT 611  or consent of instructor. Credit will not be given to both STAT 612 and STAT 653 .
  

  • STAT 613 - Linear Models

    [3]
    Matrix operations and generalized inverses, linear models, least squares theory, best linear unbiased estimation and Gauss-Markov theorem, general linear hypotheses, distribution of quadratic forms and mixed and random effects models.
    Prerequisite: Prerequisite: STAT 453 or consent of instructor.
  

  • STAT 614 - Environmental Statistics

    This is a graduate-level introduction to statistical methods used in environmental applications. The following will be emphasized throughout the course: non-parametric methods using environmental data; methods of analyzing data that are below the limit of detection; sampling designs, including stratified sampling, composite sampling and ranked set sampling; sampling to determine hot spots; trend estimation methods for uncorrelated, correlated and seasonal data; discussion of some basic ideas from spatial statistics; and environmental data analysis using statistical software.
    Prerequisite: Prerequisite: STAT 453/STAT 653  or consent of instructor.
  

  • STAT 615 - Multi-Variate Statistical Analysis

    [3]
    Multi-variate normal distribution, its properties and inference; multiple and partial correlation; Wishart distribution; Hotelling’s T2 test; tests for co-variance structure; discriminant analysis; principal components; multi-variate analysis of variance; factor analysis; and canonical correlation.
    Prerequisite: Prerequisite: STAT 453 or consent of instructor.
  

  • STAT 616 - Non-Parametric Statistics

    [3]
    Distribution-free statistics and asymptotically distribution-free statistics for the one-, two- and multi-sample problems and linear rank statistics; U-statistics and related statistics; treatment of ties; estimation of parameters based on rank statistics and other efficiency concepts and goodness-of-fit tests.
    Prerequisite: Prerequisite: STAT 453 or consent of instructor.
  

  • STAT 617 - Time Series Analysis

    [3]
    Theory and applications of time series models, auto-regressive integrated models, Box-Jenkins methodology, forecasting, seasonal models and their applications, spectral theory and estimation of time series models and time series data analysis using statistical packages.
    Prerequisite: Prerequisite: STAT 451 or consent of instructor.
  

  • STAT 618 - Applied Multi-Variate Methods

    [3]
    Multiple regression, partial and multiple correlation, multi-variate normal distribution, statistical inference for the mean vector and co-variance matrix, uni-variate and multi-variate analysis of variance, principal components, canonical correlation, discriminant analysis, factor analysis and cluster analysis. The methods will be illustrated using real data with the help of statistical packages.
    Prerequisite: Prerequisite: STAT 453 or consent of instructor.
  

  • STAT 619 - Biostatistics: Principles and Design

    [3]
    Philosophy and statistical theory involved in designing sequential, randomized medical studies, particularly, clinical trials; Scientific method; randomization principle; randomization techniques and their associated distribution theory and permutation tests; adaptive designs and ethics behind randomized studies involving human subjects; statistical methods, including survival analysis, power and sample size; dealing with multiplicities; interim monitoring techniques, including conditional power, spending functions and Brownian motion; randomized does-response studies; likelihoods and introductory Martingale theory. Both theory and applications will be stressed.
    Prerequisite: Prerequisite: STAT 601 , STAT 453 or consent of instructor.
  

  • STAT 620 - Biostatistics: Advanced Analysis

    [3]
    Theory and applications related to the statistical analysis of certain incomplete data, including survival data and longitudinal data; survival time model and censoring; generalized linear and nonlinear mixed-effect models; Kaplan-Meier estimator; Nelson-Aalen estimator; log-rank and Wilcoxon rank tests; Weibull; lognormal gamma; log-logistic distribution; parametric regression; partial likelihood; relative risk regression models; Martingale; EM-algorithm; Laplaces approximation; adaptive Gausian quadratures point; MCMC; Metropolis-Hasting algorithm; and Gibbs sampling.
    Prerequisite: Prerequisite: STAT 619  or consent of instructor.
  

  • STAT 621 - Probability Theory and Stochastic Processes I

    [3]
    Measure-theoretic approach to probability, conditional probability and random variables; distribution functions; modes of convergence; the zero-one law; probability inequalities; dependence and the Martingale theory; and Markov chains and their stationary distributions.
    Prerequisite: Prerequisite: MATH 600  or MATH 601 , STAT 611  or consent of instructor.
  

  • STAT 622 - Probability Theory and Stochastic Processes II

    [3]
    Advanced development of estimation techniques, including sufficiency, minimum variance and invariance; asymptotic properties of maximum likelihood estimators; Neyman-Pearson lemma and least favorable distributions; Bayesian inference and decision theory; and Stein estimator.
    Prerequisite: Prerequisite: STAT 612  or consent of instructor.
  

  • STAT 623 - Sequential Analysis

    [3]
    Sequential estimation, sequential probability ratio tests, operating characteristic and average sample size, efficiency of sequential testing, extensions of the probability ratio tests and sequential test.
    Prerequisite: Prerequisite: STAT 612  or consent of instructor.
  

  • STAT 625 - Spatial Statistics and Image Analysis

    [3]
    Analysis of geostatistical data, variogram, co-variogram, spatial prediction, kriging, Lattice models, Markov random fields and their use in Bayesian inference for spatial models, statistical image analysis, frequentist and Bayesian approaches and their applications. Additional topics in image analysis, such as mixture analysis, segmentation and in spatial point process theory may be covered.
  

  • STAT 633 - Methods of Statistical Computing

    [3]
    Pseudo-random number generation; sampling methods inversion; rejection sampling, ratio of uniforms; squeezing; variance reduction; importance sampling; antithetic variates; stochastic simulation; Gibbs sampling and Markov Chain Monte Carlo; resampling methods, including jackknife, bootstrap and randomization tests; use of the EM algorithm.
  

  • STAT 651 - Basic Probability

    [3]
    This is a graduate-level introduction to basic probability theory and its applications that is suitable for the applications-oriented master’s tracks and will be cross-listed with STAT 451, the undergraduate basic probability course. Emphasis will be given on problem-solving using tools of probability. The course will cover all basic notions of probability, random variables, standard discrete and continuous distributions, mean and variance, functions of random variables and central limit theorem.
  

  • STAT 652 - Stochastic Models in Operations Research

    [3]
    Stochastic programming, Markov decision processes and stochastic inventory models and sequential stochastic games.
    Prerequisite: Prerequisite: MATH 650 , MATH 681 , STAT 611  or consent of instructor.
  

  • STAT 653 - Basic Mathematical Statistics

    [3]
    This is a graduate-level introduction to basic mathematical statistics and its applications that is suitable for the applications-oriented master’s tracks. It will be cross-listed with STAT 453, the undergraduate basic mathematical statistics course. Emphasis will be given on problem-solving using tools of mathematical statistics. The course will cover all basic notions of estimation, tests, confidence intervals, hypothesis testing, linear models, analysis of variance, control charts and non-parametric procedures.
    Prerequisite: Prerequisite: STAT 651  or consent of instructor.
  

  • STAT 690 - Statistics Seminars

    [0]
  

  • STAT 696 - Mathematics Practicum

    [1-4}
  

  • STAT 699 - Independent Study in Statistics

    [1-6]
    One-on-one instruction of a graduate student by a member of the faculty. The topic and format of the course are by mutual agreement between the professor and the student, subject to approval by the graduate program director.
  

  • STAT 700 - Special Topics in Statistical Methods and Data Analysis

    [1-3]
  

  • STAT 710 - Special Topics in Mathematical Statistics and Statistical Inference

    [1-3]
  

  • STAT 750 - Introduction to Interdisciplinary Consulting

    [3]
    A course designed to train students in the art of interdisciplinary consulting and prepare them for careers as professional statisticians.
    Prerequisite: Prerequisites: STAT 601 , STAT 602 , STAT 651 , STAT 653 , familiarity with SAS and S-Plus or consent of instructor.
  

  • STAT 799 - Master’s Thesis Research

    [1-6]
    Master’s thesis research under the direction of a UMBC MEES faculty member.
    Note: Six credit hours are required for the master’s degree.
  

  • STAT 898 - Pre-Candidacy Doctoral Research

    [1-6]
    Research on doctoral dissertation conducted under the direction of a faculty advisor before candidacy.
  

  • STAT 899 - Doctoral Dissertation Research

    [9]
    Doctoral dissertation research under the direction of a UMBC MEES faculty member.
    Prerequisite: Admission to Doctoral Candidacy Required
    Note: A minimum of 18 credit hours are required. This course is repeatable
  

  • STAT 7700 - Master’s Special Study

    [1]
  

  • STAT 8800 - Doctoral Special Study

    [1]

Technical Management
  

  • TECH 650 - Project Management Fundamentals

    [3]
    Students learn the fundamentals of managing projects in a systematic way. These fundamentals can be applied within any industry and work environment and will serve as the foundation for more specialized project management study. Principles and techniques are further reinforced through practical case studies and team projects in which students simulate project management processes and techniques.
    Course ID: 054307
    Components: Lecture
    Grading Method: R
  

  • TECH 652 - Management, Leadership, and Communication

    [3]
    In this course, students learn effective management and communication skills through case study-analysis, reading, class discussion and role-playing. The course covers topics such as effective listening, setting expectations, delegation, coaching, performance, evaluations, conflict management, negotiation with senior management and managing with integrity.
    Course ID: 054309
    Components: Lecture
    Grading Method: R
  

  • TECH 654 - Leading Teams and Organizations

    [3]
    In this course, students analyze leadership case studies across a wide range of industries and environments to identify effective leadership principles that may be applied in their own organizations. Students learn how to influence people throughout their organization, lead effective teams, create an inclusive workplace, use the Six Sigma process, implement and manage change and develop a leadership style.
    Course ID: 054311
    Prerequisite: TECH 652 or BTEC 665
    Components: Lecture
    Grading Method: R

UMB Department of Biochemistry and Molecular Biology, School of Medicine (MBIC)
  

  • GPLS 601 - Mechanisms in Biomedical Sciences: From Genes to Disease

    [8]
    This course is a comprehensive overview of current knowledge in cellular, molecular, and structural biology. This course provides the background necessary for subsequent specialized studies in biomedical research in a concentrated program. The GPILS Core Course is organized into 10 sections that span molecular biology, genetics, proteins, pharmacology, metabolism, membranes and organelles, protein processing, membrane signaling, cell signaling, immunobiology, and development. The format is highly interactive and includes:

    •      lectures presenting creative, cutting-edge approaches to investigating fundamental, current biomedical questions, together with review of fundamental principles of molecular and cellular biology;

    •      vertically integrated topics that tie together the study of individual genes, proteins, cellular function, and associated clinical disorders;

    •      emphasis on development and critical evaluation of scientific hypotheses;

    •      introduction to state-of-the-art techniques;

    •      mentored discussions of primary papers;

    •      topic-specific seminars, including cancer, neuroscience, and drug development/gene therapy.
  

  • GPLS 608 - Seminar

    [1]
    This course requires that students attend eight research seminars during the semester either at the UMB Department of Biochemistry and Molecular Biology or the UMBC Department of Chemistry and Biochemistry. Research seminars will be given by local, national and international speakers, and synopses of the seminars are prepared by each student and turned in to the instructor.
  

  • GPLS 609 - Lab Rotations

    [1]
    Students gain experience in a variety of techniques and become familiar with the faculty members and their research. Doctoral students generally complete two or three rotations in different laboratories in the program. Rotations usually last six to eight weeks.
  

  • GPLS 616 - Molecular Mechanisms of Signal Transduction

    [3]
    This twice-weekly literature, discussion and lecture course covers mechanisms of hormone action upon target cells, with emphasis on the molecular mechanisms by which hormones mediate their cellular effects.
    Prerequisite: Prerequisites: Completion of GPLS core curriculum, GPLS 601, GPLS 602 and GPLS 603.
  

  • GPLS 618 - Readings/Special Topics

    [1]
  

  • GPLS 622 - Intro to Biostatistics

    [3]
    This course is designed to develop an understanding of statistical principles and methods as applied to human health and disease. Topics include: research design; descriptive statistics; probability; distribution models; binomial, Poisson and normal distribution; sampling theory and statistical inference.
  

  • GPLS 625 - Ion Channels

    [3]
    Covers the role of voltage- and receptor-gated ion channels in cell function. Although the emphasis is on structure and function of channels in excitable tissues such as nerve and muscle, students gain insight into the rapidly developing field of ion channel function in non-excitable cells such as lymphocytes, transformed cells and glial cells and the roles of ion channels in development.
  

  • GPLS 626 - Membrane Carriers Transporters

    [2]
    This course is designed to prepare students for advanced study and laboratory research on the mechanisms by which ions and small molecules are transported across biological membranes. The course starts with consideration of the general methodology, thermodynamics, and kinetics of transmembrane, transcellular, and transepithelial ion transport. The focus then shifts to the biochemistry and molecular and structural biology of common plasma membrane active transport systems for ions, nutrients, and neurotransmitters. It also covers the relationships and interactions between transport proteins in the plasma membrane and intracellular membranes.
  

  • GPLS 630 - Fundamentals of Biostatistics

    [3]
    This course covers most of the basic types of analysis procedures used for continuous and discrete variables. Topics include statistical inference (p-values, confidence intervals, hypothesis tests), t-tests, chi-square tests, power calculations, nonparametric methods, simple and multiple linear regression, ANOVA, logistical regression, and survival analysis.
  

  • GPLS 635 - Bacterial Genetics

    [4]
    Covers induction, expression and selection of mutants; molecular basis of mutations; transfer of genetic information by transformation, transduction and conjugation; complementation and recombination in phage and bacteria; plasmids; and recombinant DNA. Two lectures and two laboratory periods per week deal with the genetics of bacteria and bacterial viruses.
  

  • GPLS 665 - Cancer Biology: From Basic Research to the Clinic

    [3]
    This course is designed to introduce students to both the biology of specific cancers and to how patients with these diseases are managed and treated. The course consists of twice-weekly lectures in which a basic or translational scientist is paired with a clinician to describe a specific disease, and the major questions that need to be answered to improve treatments. Thus, the lectures alternate between lectures on basic biology and clinical management of cancer patients. The first half of the course deals with hereditary cancers and the second half covers sporadic cancers. In addition to attending the lectures, students attend one relevant tumor board conference (during which clinical cases are presented and discussed) each week. Each student is assigned a clinical mentor who helps identify a clinical question or problem of current interest, and each student writes a concise, focused mini-review of the literature and issues related to this question (guidelines are provided).
  

  • GPLS 701 - Advanced Molecular Biology

    [3]
    This core course for the biochemistry program covers advanced topics in molecular biology and genetics, taught principally from current primary literature. A combination of lectures and student-directed seminars address recent developments in DNA/RNA metabolism and regulation of gene expression, while additional sessions explore genetics and molecular contributions to control of cellular function and disease.
  

  • GPLS 709 - Advanced Biochemistry

    [3]
    This advanced core course for the biochemistry program emphasizes protein structure and function, including the following topics: protein folding and stability; thermodynamics; allosteric interactions; protein structure/dynamics, the chemistry of enzyme mechanisms; steady-state and pre-steady state kinetics; and methods used for characterizing proteins and enzymes, including circular dichroism, nuclear magnetic resonance, X-ray diffraction, protein fluorescence and stopped-flow techniques. The course includes problem sets and two exams.
  

  • GPLS 710 - Microbial Pathogenesis

    The aim of this course is to provide groundwork in basic principles of bacterial pathogenesis and to illustrate some of the current research topics and methodologies used in this field. It is assumed that students will already be somewhat familiar with fundamentals of bacterial structure and metabolism. The first part of the course covers basic concepts, while the second part examines selected specific organisms and topics in further detail. Classes consist of a mixture of lecture material and discussion of research papers, with the idea of familiarizing students with the basic facts and ideas of a particular subject and exploring methods of study and research questions on that topic. It is expected that students will read the assigned research papers before class and will participate in class discussions of the material. There are two exams covering the material discussed in classes - the first just before spring break and the second toward the end of the semester. Following the second exam, students make presentations based on assigned reading and research topics.
  

  • GPLS 713 - Graduate Biochemistry Seminar

    [2]
    Student taking this required course will examine and then present research seminars on current topics in biochemistry and molecular biology. Special topics will vary each semester and are chosen in advance by the instructor. In addition to the quality of the scientific presentation, the course will also stress the critical evaluation of the scientific work by the presenter and the members of the class; thus, participation in weekly discussions by all students is an essential aspect of the course.
  

  • GPLS 714 - Muscle: Contractility and Excitation

    [3]
    This course offers a comprehensive description of the basic physiology, biochemistry and biophysics of cardiac, skeletal and smooth muscle. Topics include: ultrastructure of skeletal muscle, mechanical and biochemical features of the crossbridge cycle in contraction, excitationcontraction coupling, calcium-induced calcium release in cardiac muscle, physiology and pharmacology of smooth muscle.
  

  • GPLS 715 - Muscle Cell Biology and Development

    [3]
    This course considers the developmental biology of muscle, including its innervation and plasticity. The course begins with a discussion of the factors controlling the proliferation and differentiation of myoblasts. Next is a consideration of fiber type determination, its relationship to use, and the effects of hypertrophy and atrophy on muscle. The structure, function and formation of the neuromuscular junction and its relationship to the organization of structures in the extra-junctional region form the next set of topics. Emphasis is placed on the extra-cellular matrix and the cytoskeleton. The last part of the course deals with the relationship of activity and hormonal influences to the biochemical properties of muscle. The course meets twice weekly and consists of one lecture and one session for student oral presentations and discussion of assigned research pertinent to the lecture topic.
  

  • GPLS 716 - Applied Bioinformatics

    [2]
    The explosive growth of data derived from genomic and postgenomic projects has revolutionized biology and medicine. As a result, a solid foundation in computational biology and bioinformatics is now essential for all practitioners of biological and biomedical research. This course emphasizes both the theory and application of fundamental computer-based approaches to sequence analysis, data mining, integration, and interpretation of data related to genes and their function. Using a hands-on problem-based learning approach, students acquire familiarity with computational tools useful for analysis of the structure, function, and evolution of nucleic acids and proteins.
  

  • GPLS 790 - Advanced Cancer Biology

    [3]
    This course introduces students to the fundamentals of cancer from diagnosis to treatment, as well as the latest research discoveries. The course begins with the biology of cancer cells, the stages of cancer, and the types of tumors, and ends with topics related to animal models for studying cancer. Lectures include tumor suppressors, oncogenes, signal transduction, disruption of growth control networks, DNA damage, oncopharmacology, drug design, robotics, and common forms of cancer.
  

  • GPLS 799 - Master’s Research

    [2-9]

Science, Technology, Engineering and Mathematics Education Courses
  

  • STEM 506 - The Designed World

    [3]

    Drawing upon the idea that the natural world is understandable and predictable, and that science is durable but cannot provide complete answers to all questions, students will examine their own world views of science. This course will assist students with the fundamental abilities and concepts to do scientific inquiry, including designing a solution or product, implementing a proposed design, evaluating completed technological designs or products, and communicating the process of technological design.

     
  

  • STEM 509 - Environmental Engineering Design

    [3]
    This course is part of the UMBC Master of Arts in Education program with a concentration in Science, Technology, Engineering, and Mathematics (STEM). Students will learn the main areas of concern for environmental engineering including: calculations, ecological concepts, risk assessment, design and modeling of environmental systems and solutions to sustainability. Students will explore past environmental calamities focusing on causes, warnings, prevention, and responses. Students will participate in the design process to explore possible current environment issues and possible solutions. The students will also use the applications of environmental engineering design to K-12 classrooms through the development of case studies.
  

  • STEM 533 - Culturally Responsive Teaching in Stem

    [3]

    Culturally responsive teaching is based on the belief that culture is central to student learning. Culture refers to the integrated patterns of human behavior that include language, thoughts, communication, actions, customs, beliefs, values, and norms of racial, ethnic, religious, or social groups (Educational Leadership Project, 2005). This course provides the theories and research related to culturally responsive teaching and examines the classroom practices, such as interdisciplinary units, using real-world connections, creating safe, respectful environments and use of explicit instruction, to assist course participants to understand their own cultural identity and be able to make teaching and learning more relevant and effective in their classrooms. The students in this course will be able to identify and examine issues pertinent specifically to STEM-content related issues relating to gender, race, ethnicity and English Language Learners as well as other social groups.

     
  

  • STEM 550 - Emerging TEchnologies and their Applications

    [3]
    This course is part of the UMBC Master of Arts in Education program with a concentration in Science, Technology, Engineering, and Mathematics (STEM). Students will learn the main areas of technology education including: developing the knowledge and skills to be technologically literate (including understanding the nature of technology, attributes of design, relationship between technology and society), learn how students learn technology, and evaluate and design curriculum for technology education. Students will explore the seven areas of technology and the impact of new technologies including how it impacts society and the possible societal fears or misunderstandings. Students will participate in the design process by revisiting the game design from a previous course (The Designed World) through critique of both their final product and products new to the market. The students will also critique and develop unit plans and curriculum materials that emphasize technology and its role in STEM education.
 

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