Teaching, with Teacher Certification in Mathematics (Preschool-Grade 12) and Teacher of Students with Disabilities (M.A.T.) Graduate (Combined B.S./M.A.T.) - 2015 University Catalog

The Bachelor's/MAT Dual-Certification Inclusive Education Program provides students with the opportunity to receive both a bachelor's and Master of Arts in Teaching (MAT) degree with teacher certification in both general education and special education.  The program is designed to help teachers develop competencies needed to teach students who have disabilities along with those who do not.

In this program, students complete general education and major requirements and an initial set of coursework in education as undergraduates. As graduate students, they will complete the coursework in education and conduct their fieldwork and student teaching.

TEACHING (MATH & STUDENTS w/DISAB)

Complete 36 semester hours including the following 5 requirement(s):

  1. GRADUATE PROFESSIONAL SEQUENCE PART I

    Complete 2 courses:

    SASE 521 Inclusive iSTeM for the Adolescent Learner II (3 hours lecture) 3
    SPED 586 Transition Services for Students with Disabilities (3 hours lecture) 3
  2. GRADUATE PROFESSIONAL SEQUENCE PART II

    Complete the following 2 requirement(s):

    1. Complete for 3 semester hours.

      MATH 519 Teaching Mathematics (3 hours lecture) 3
    2. Complete 2 requirement(s):

      1. Complete the following 2 courses:

        SASE 526 Teaching for Learning I (3 hours lecture) 3
        SASE 527 Fieldwork (3 hours lecture) 3
      2. Complete 1 course from the following:

        ECEL 691 Issues, Policies and Trends in Inclusive Education (3 hours lecture) 3
        SPED 691 Issues, Policies and Trends in Inclusive Education (3 hours lecture) 3
  3. GRADUATE PROFESSIONAL SEQUENCE PART III

    Complete the following 2 courses:

    SASE 529 Student Teaching (6 hours lab) 6
    SASE 543 Teaching for Learning II (3 hours lecture) 3
  4. ADDITIONAL GRADUATE COURSES

    The following coursework is completed as part of the undergraduate component.

    1. Complete 2 courses:

      SASE 520 Inclusive iSTEM for the Adolescent Learner I (3 hours lecture) 3
      SPED 584 Assessment and Evaluation in the Inclusive Classroom 2-3
    2. Complete 1 course from the following with advisor approval:

      MATH 521 Real Variables I (3 hours lecture) 3
      MATH 522 Real Variables II (3 hours lecture) 3
      MATH 525 Complex Variables I (3 hours lecture) 3
      MATH 526 Complex Variables II (3 hours lecture) 3
      MATH 530 Mathematical Computing (3 hours lecture) 3
      MATH 531 Abstract Algebra I (3 hours lecture) 3
      MATH 532 Abstract Algebra II (3 hours lecture) 3
      MATH 535 Linear Algebra I (3 hours lecture) 3
      MATH 536 Linear Algebra II (3 hours lecture) 3
      MATH 540 Probability (3 hours lecture) 3
      MATH 551 Topology (3 hours lecture) 3
      MATH 554 Projective Geometry (3 hours lecture) 3
      MATH 560 Numerical Analysis (3 hours lecture) 3
      MATH 564 Ordinary Differential Equations (3 hours lecture) 3
      MATH 566 Partial Differential Equations (3 hours lecture) 3
      MATH 568 Applied Mathematics: Continuous (3 hours lecture) 3
      MATH 569 Applied Mathematics: Discrete (3 hours lecture) 3
      MATH 580 Combinatorial Mathematics (3 hours lecture) 3
      MATH 581 Graph Theory (3 hours lecture) 3
      MATH 584 Operations Research (3 hours lecture) 3
      MATH 585 Fundamentals of Scientific Computing (3 hours lecture) 3
      MATH 586 Fundamentals of Mathematical Models (3 hours lecture) 3
      MATH 587 Fundamentals of Optimization (3 hours lecture) 3
      MATH 588 Professional Science Master Mini-Projects (6 hours lecture) 6
      MATH 590 Advanced Topics (3 hours lecture) 3
      MATH 591 Applied Industrial Mathematics (3 hours lecture) 3
      STAT 541 Applied Statistics (3 hours lecture) 3
      STAT 542 Statistical Theory I (3 hours lecture) 3
      STAT 543 Statistical Theory II (3 hours lecture) 3
      STAT 544 Statistical Computing (3 hours lecture) 3
      STAT 545 Practicum in Statistics I 3
      STAT 546 Non-Parametric Statistics (3 hours lecture) 3
      STAT 547 Design and Analysis of Experiments (3 hours lecture) 3
      STAT 548 Applied Regression Analysis (3 hours lecture) 3
      STAT 549 Sampling Techniques (3 hours lecture) 3
  5. COMPREHENSIVE EXAMINATION

    In the term that you will sit for exam, register for - which matches your major & advisor. Successfully pass exam.

    GRAD CMP Comprehensive Examination 0

Course Descriptions:

ECEL691: Issues, Policies and Trends in Inclusive Education (3 hours lecture)

The culminating experience for the BA/MAT Dual Certification programs, this course focuses on policies, issues, and trends related to the education of students in inclusive settings. Relevant sociological and cultural perspectives focused on the social construction of dis/ability are examined as well as their implications for the schools. Students synthesize, analyze, and evaluate issues of relevance to inclusive education that will impact their professional careers as teachers in inclusive environments and the future of inclusive education. Students also conduct an empirical research project on inclusion. 3 sh.

Prerequisites: Completion of 12 graduate credits in the program.

GRADCMP: Comprehensive Examination

This course is a placeholder for matriculated master's students planning to take the departmental Comprehensive Examination. Successful completion of the Comprehensive Examination will result in a grade of P, unsuccessful students will receive a grade of NC. Students who do not successfully complete the Comprehensive Examination will be required to register for this placeholder course in each term for which they plan to take the examination (limited to three). 0 sh.

Prerequisites: Matriculation in Master's degree program required.

MATH519: Teaching Mathematics (3 hours lecture)

Selection, organization, and presentation of secondary mathematics, classroom activities, lesson planning, techniques of motivation, evaluation, multi-sensory aids, principles of learning, assessment, and applications of technology to classroom teaching. 3 sh.

MATH521: Real Variables I (3 hours lecture)

Real number system, Lebesgue measure and integration, differentiation, Fourier series, LP, metric, normed vector, Banach and Hilbert spaces. 3 sh.

Prerequisites: MATH 426 and permission of graduate program coordinator.

MATH522: Real Variables II (3 hours lecture)

Real number system, Lebesgue measure and integration, differentiation, Fourier series, LP, metric, normed vector, Banach and Hilbert spaces. 3 sh.

Prerequisites: MATH 521, permission of graduate program coordinator.

MATH525: Complex Variables I (3 hours lecture)

Integration and differentiation in the complex domain, Cauchy's theorem, Cauchy's integral formula, Laurent expansion, residues, elements of conformal mapping, series and product representations. 3 sh.

Prerequisites: MATH 426 and permission of graduate program coordinator.

MATH526: Complex Variables II (3 hours lecture)

Integration and differentiation in the complex domain, Cauchy's theorem, Cauchy's integral formula, Laurent expansion, residues, elements of conformal mapping, series and product representations. 3 sh.

Prerequisites: MATH 525, permission of graduate program coordinator.

MATH530: Mathematical Computing (3 hours lecture)

Introduction to mathematical computing techniques using a computer algebra system and algorithmic approach to solving mathematical problems. Mathematical applications taken from various areas of mathematics, the sciences, engineering, and business. 3 sh.

Prerequisites: Permission of the graduate program coordinator or consent of the instructor.

MATH531: Abstract Algebra I (3 hours lecture)

Basic algebraic structures including groups, rings, fields, modules and lattices. 3 sh.

Prerequisites: MATH 431 and permission of graduate program coordinator.

MATH532: Abstract Algebra II (3 hours lecture)

Basic algebraic structures including groups, rings, fields, modules and lattices. 3 sh.

Prerequisites: MATH 531, permission of graduate program coordinator.

MATH535: Linear Algebra I (3 hours lecture)

Vector spaces and linear transformations, including inner product, matrix representations, binary and quadratic forms, eigenvectors, canonical forms, and functions of matrices. 3 sh.

Prerequisites: MATH 335 and permission of graduate program coordinator.

MATH536: Linear Algebra II (3 hours lecture)

Vector spaces and linear transformations, including inner product, matrix representations, binary and quadratic forms, eigenvectors, canonical forms, and functions of matrices. 3 sh.

Prerequisites: MATH 535, permission of graduate program coordinator.

MATH540: Probability (3 hours lecture)

Sample spaces and events, combinatorial analysis, conditional probability and stochastic independence, random variables and probability distributions, expected value and variance, probability generating functions, continuous random variables. 3 sh.

Prerequisites: MATH 340 and permission of graduate program coordinator.

MATH551: Topology (3 hours lecture)

Basic point-set topology, topological spaces, homeomorphisms, compactness, connectedness, separation properties, uniformities, metrizability, introductory algebraic topology, homology groups and homotopy. 3 sh.

Prerequisites: MATH 425, and permission of graduate program coordinator.

MATH554: Projective Geometry (3 hours lecture)

Projective planes and spaces are studied by synthetic and analytic approaches. Topics covered include the theorems of Desargues and Pappus, harmonic sequences, projectivities, coordinatization, finite planes, and conics. 3 sh.

Prerequisites: MATH 335 and permission of graduate program coordinator.

MATH560: Numerical Analysis (3 hours lecture)

Error analysis, interpolation and approximation theory, numerical solution of linear and nonlinear equations, numerical differentiation and integration, numerical solution of differential equations. 3 sh.

Prerequisites: MATH 335, and permission of graduate program coordinator.

MATH564: Ordinary Differential Equations (3 hours lecture)

Linear and nonlinear equations, Green's functions, power series solutions, autonomous systems, existence and uniqueness, singularities, Sturm-Liouville systems. 3 sh.

Prerequisites: MATH 335, and 420, and permission of graduate program coordinator.

MATH566: Partial Differential Equations (3 hours lecture)

First order equations, separation of variables, series solutions, hyperbolic, parabolic and elliptic equations, characteristics, transform methods. 3 sh.

Prerequisites: MATH 335, and 420, and permission of graduate program coordinator.

MATH568: Applied Mathematics: Continuous (3 hours lecture)

Formulation, manipulation and evaluation of mathematical models of continuous systems. Topics selected from: conservation principles and the classical equations of mathematical physics, applications of the qualitative and quantitative theory of ordinary and partial differential equations, optimization, calculus of variations, stability theory, stochastic models. 3 sh.

Prerequisites: MATH 335, and 340, and 420, and 425, and permission of graduate program coordinator.

MATH569: Applied Mathematics: Discrete (3 hours lecture)

Introduction to the basic ideas of discrete mathematics and its applications. Counting principles, permutations, combinations, algorithms, complexity, graphs, trees, searching and sorting, recurrence relations, generating functions, inclusion-exclusion, the pigeonhole principle, chromatic number, eulerian chains and paths, hamiltonian chains and paths, flows in networks, finite Markov chains. 3 sh.

Prerequisites: MATH 335, and 340, and 425, and permission of graduate program coordinator.

MATH580: Combinatorial Mathematics (3 hours lecture)

Arrangements and selections, binomial coefficients, Stirling numbers, generating functions, recurrence relations, inclusion-exclusion, Polya enumeration formula, combinatorial graph theory, combinatorial geometries. 3 sh.

Prerequisites: MATH 222 and graduate program coordinator's permission.

MATH581: Graph Theory (3 hours lecture)

Graphs, digraphs, and trees. Connectivity, separability, planarity, and colorability. Cliques, independent sets, matchings, flows and tours. Graphs as mathematical models; graph algorithms. 3 sh.

Prerequisites: MATH 222, and 335, and graduate program coordinator's permission.

MATH584: Operations Research (3 hours lecture)

An in-depth study of one or at most two topics in operations research, selected from linear programming and game theory, linear and nonlinear programming, queuing theory, inventory theory, simulation models. 3 sh.

Prerequisites: MATH 425 and STAT 440 and permission of graduate program coordinator.

MATH585: Fundamentals of Scientific Computing (3 hours lecture)

Theory and implementation of mathematical computing techniques. This course will present basic programming and graphing techniques to analyze mathematical models. Students will learn basic algorithm design, programming paradigms, simulation techniques, visualization software, and typesetting software for science and mathematics. 3 sh.

Prerequisites: MATH 420 and permission of the Graduate Program Coordinator.

MATH586: Fundamentals of Mathematical Models (3 hours lecture)

The course investigates meaningful and practical problems across various industry related disciplines including mathematical sciences, engineering, economics, operation research and life sciences. Students will learn how to identify problems, construct or select developed models, collect and analyze data, and draw appropriate conclusions. The development of appropriate mathematical models used to study applied case problems originating from industry interest will be stressed as well as interpretation of mathematical results in that context. 3 sh.

Prerequisites: MATH 585 and STAT 583 and permission of graduate program coordinator.

MATH587: Fundamentals of Optimization (3 hours lecture)

Introduction to applied optimization in various settings, both continuous and discrete. Topics selected from linear programming, non-linear programming, network optimization models, and feedback control with an emphasis on applications to business management, economics, game theory, and finance. The course will be team-taught, with the various areas of optimization introduced by faculty with expertise in that field. 3 sh.

Prerequisites: MATH 585 and STAT 583 and permission of Graduate Coodinator.

MATH588: Professional Science Master Mini-Projects (6 hours lecture)

Students working in teams will be assigned problems selected from professional case studies and may include problems of current interest supplied by collaborating industries and/or advisory board members. Solution methodology will vary from problem to problem and will require the wide breadth of mathematical tools covered in the prerequisite courses. These include discrete and continuous modeling, optimization methods, and data analysis. Central to the professional experience, students will present problem statement, solution methodology, and results during class time. Emphasis will be placed on incorporating the skills developed in the PSM plus courses. Specifically, these skills involve understanding goals, leadership and teamwork, communication skills, marketing the project, discipline, flexibility, innovation, special appropriate technologies, quality of project outcomes, ethics (as applicable), and meeting potential employer expectations. 6 sh.

Prerequisites: MATH 585, MATH 586, MATH 587, STAT 583 and permission of the Graduate Program Coordinator.

MATH590: Advanced Topics (3 hours lecture)

An in-depth study of a topic or topics selected from areas such as algebra, analysis, geometry, probability and statistics, and applied mathematics, with special emphasis upon recent developments in the field. May be repeated once for a maximum of 6.0 credits as long as the topic is different. 3 sh.

Prerequisites: Graduate program coordinator's permission.

MATH591: Applied Industrial Mathematics (3 hours lecture)

Formulation, modeling, and solution of mathematical problems from engineering, science and business. Topics include statistical distributions, Monte Carlo method, function fitting, transforms optimization, regression analysis, cost-benefit analysis, ordinary differential equations, partial differential equations, numerical methods, divided differences, splines, Galerkin's method, and finite elements. 3 sh.

Prerequisites: MATH 335, MATH 425, MATH 530, STAT 440 or permission of graduate program coordinator.

SASE520: Inclusive iSTEM for the Adolescent Learner I (3 hours lecture)

This course provides an introduction to integrative STEM education (e.g., Science, Technology, Engineering, and Mathematics) as a tool to advance student learning in the STEM content areas, creativity, and innovation. Teachers today have a strong commitment to teaching the subject matter as listed in their content-area standards. However, given the changing trends in education and the push for technology integration, teachers and students are facing rapid change. This course addresses the essential question, "How do you inspire learning and creativity in all students according to the standards while maintaining balance in your core curriculum?" Through exploration of "big ideas" in invention and innovation, teacher candidates will begin to answer this question. 3 sh.

Prerequisites: SPED 579 and SPED 568.

SASE521: Inclusive iSTeM for the Adolescent Learner II (3 hours lecture)

This course examines research and pedagogy for integrative STEM teaching and learning. In this course, teacher candidates learn to systematically apply design-based inquiry and project-based learning, and national STEM (e.g., Science, Technology, Engineering, and Mathematics) standards and integrative curricula. The setting for the study of inclusive iSTeM and design-based inquiry will focus on initiating iSteM teaching and learning in inclusive middle/secondary math and science classrooms, with particular attention to improving access to the general education STEM curriculum for students with disabilities and English language learners. Students will demonstrate their learning through design and inquiry projects, field-based, universally-designed instructional planning and implementation, class discussions, and writing assignments. 3 sh.

Prerequisites: SPED 579 and SPED 568 and SASE 522.

SASE526: Teaching for Learning I (3 hours lecture)

This is the first course in a two-semester sequence (SASE 526, SASE 543). This course focuses on developing classroom practices necessary for student teaching and the beginning of a professional career in teaching, building from the knowledge and skills developed in previous courses in the professional sequence. In conjunction with SASE 527-Fieldwork, students have the opportunity to observe in classrooms and to do individual, small group, and whole class teaching. Students investigate democratic classroom practice by focusing on curriculum development; creating a positive, well-structured climate for learning in their classrooms; learning and practicing techniques for effective classroom management; and choosing appropriate teaching strategies and assessments to create successful learning experiences for their students. Previous course CURR 526 effective through Spring 2014. 3 sh.

Prerequisites: SASE 505 or EDFD 505; SASE 509 or EDFD 509; SASE 516 or EDFD 516; SASE 517; SASE 518; READ 501. Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

SASE527: Fieldwork (3 hours lecture)

Students spend 60 hours, or approximately one day per week, in a selected public school. Activities include, but are not limited to, observing classroom teachers, facilitating small group and individual instruction, participating in after-school activities, tutoring, attending department meetings, shadowing and interviewing students and teachers, lesson planning and teaching, and assessing student work. May be repeated once for a maximum of 6.0 credits. Previous course CURR 527 effective through Spring 2014. 3 sh.

Prerequisites: SASE 505 or EDFD 505; and SASE 509 or EDFD 509; and SASE 516 or EDFD 516; and SASE 517; and SASE 518; and EDFD 519 or SASE 519; and READ 501. Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

SASE529: Student Teaching (6 hours lab)

Full time student teaching in the public schools of New Jersey for the duration of a semester is required of all students who complete the regular program of certification requirements. 6 hour lab requirements. May be repeated once for a maximum of 12.0 credits. Previous course CURR 529 effective through Spring 2014. 6 sh.

Prerequisites: SASE 505 or EDFD 505; and SASE 509 or EDFD 509; and SASE 516 or EDFD 516; and SASE 517; and SASE 518; and SASE 519 or EDFD 519; and SASE 526; and SASE 527; and READ 501; and content area methods course(s). Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

SASE543: Teaching for Learning II (3 hours lecture)

This is the second course in a two-semester sequence (SASE 526, SASE 543). This course focuses on putting into practice all the knowledge and skills students have developed throughout their professional sequence in their full-time, supervised student teaching experience. A primary focus is on planning and implementing curriculum. In addition to curriculum planning and using appropriate instructional and assessment strategies, students learn about the impact of the school and classroom culture and climate on student learning and on relationships between and among students, teachers, and other professionals in school. May be repeated once for a maximum of 6.0 credits. Previous course CURR 543 effective through Spring 2014. 3 sh.

Prerequisites: SASE 505 or EDFD 505; and SASE 509 or EDFD 509; and SASE 516 or EDFD 516; and SASE 517; and SASE 518; and SASE 526; and SASE 527; and READ 501; and content area methods course(s). Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

SPED584: Assessment and Evaluation in the Inclusive Classroom

This course is designed to be an introduction for pre-service teachers in the field of Special Education assessment and accountability. The course will introduce students to elements of traditional assessment, including record keeping, grading, objective and essay testing, theories of validity as well as authentic, performance, and portfolio assessment. The keeping of anecdotal records, inclusion, heterogeneous groups, and accommodations will also be components of this course. 2 - 3 sh.

Prerequisites: SPED 579. Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

SPED586: Transition Services for Students with Disabilities (3 hours lecture)

This course will focus on a Research-Based and Teacher-Tested Support Model for planning and implementing transition services for students with disabilities. Successful transition services will allow students to build the bridges toward becoming independent self advocates with the insights, skills, knowledge, and learning techniques for successful transition from school to adult life. 3 sh.

Prerequisites: SPED 579. Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

SPED691: Issues, Policies and Trends in Inclusive Education (3 hours lecture)

The culminating experience for the BA/MAT Dual Certification programs, this course focuses on policies, issues, and trends related to the education of students in inclusive settings. Relevant sociological and cultural persepectives focused on the social construction of disability are examined as well as their implications for the schools. Students synthesize, analyze, andevaluate issues of relevance to inclusive education that will impact their professional careers as teachers in inclusive environments and the future of inclusive education. Students also conduct an empirical research project on inclusion. 3 sh.

Prerequisites: Completion of 12 Graduate credits in the program. Students must be enrolled in a Master of Arts in Teaching (MAT), Instructional Teaching Certificate (CRI), Educational Services Certificate (CRE) or Master of Education (MED).

STAT541: Applied Statistics (3 hours lecture)

Review of estimation and hypothesis testing for one sample and two sample problems; introduction to non-parametric statistics and linear regression; fundamental principles of design, completely randomized design, randomized block design, latin square, and 2 factor design. 3 sh.

Prerequisites: STAT 330 or STAT 443 and permission of graduate program coordinator.

STAT542: Statistical Theory I (3 hours lecture)

Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chi-squared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, Neyman-Pearson Lemma, likelihood ratio tests. The impact of the above theory on areas such as regression analysis, analysis of variance and analysis of discrete data. 3 sh.

Prerequisites: STAT 541 and permission of graduate program coordinator.

STAT543: Statistical Theory II (3 hours lecture)

Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chi-squared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, Neyman-Pearson Lemma, likelihood ratio tests. The impact of the above theory on areas such as regression analysis, analysis of variance and analysis of discrete data. 3 sh.

Prerequisites: STAT 542 and permission of graduate program coordinator.

STAT544: Statistical Computing (3 hours lecture)

Computer systems for data analysis and data graphics, and intermediate level statistical methodology are investigated. Several statistical computing packages are utilized and evaluated. 3 sh.

Prerequisites: STAT 541 or STAT 548, and CMPT 183, and permission of graduate program coordinator.

STAT545: Practicum in Statistics I

An applied experience in which students work with practitioners in industry, government or research organizations utilizing statistical techniques in a research setting. Students will work with statisticians on projects involving experimental design and data collection as well as the analysis and interpretation of the data. May be repeated once. 3 sh.

Prerequisites: STAT 541, STAT 544, and STAT 547 or STAT 548, and permission of graduate program coordinator.

STAT546: Non-Parametric Statistics (3 hours lecture)

Selected distribution-free tests and estimation techniques including sign, Kolmogorov-Smirnov, Wilcoxon signed rank, Mann-Whitney, Chi-square, rank correlation, Kendall's Tau, Kruskal-Wallace, Friedman, McNemar, and others. 3 sh.

Prerequisites: STAT 330 and permission of graduate program coordinator.

STAT547: Design and Analysis of Experiments (3 hours lecture)

Fundamental principles of design; fixed, random and mixed models; factorial designs; designs with restricted randomization; split-plot design; confounding; fractional replication; experimental and sampling errors. 3 sh.

Prerequisites: STAT 541 or STAT 548, and permission of graduate program coordinator.

STAT548: Applied Regression Analysis (3 hours lecture)

Fitting equations to data; matrices, linear regression; correlation; analysis of residuals; multiple regression; polynomial regression; partial correlation; stepwise regression; regression and model building; regression applied to analysis of variance problems; introduction to nonlinear regression. 3 sh.

Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.

STAT549: Sampling Techniques (3 hours lecture)

Sampling and survey methodology; basic sampling theory; simple, stratified, random, cluster, systematic and area sampling. Sampling errors and estimation procedures. 3 sh.

Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.