Timeroom: Fall 2022

Displaying 101 - 110 of 153 Results for: Subject = MATH
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 700 (01) - Introduction to Mathematics Education

Intro to Mathematics Education

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 10849
General background information about mathematics education, such as theories of learning and teaching mathematics, mathematics curricula, classroom management, and techniques for the teaching and learning of mathematics that are common to all levels of mathematics education K-12. Prereq: MATH 426 and EDUC 500; or permission.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Sheree Sharpe
Start Date End Date Days Time Location
8/29/2022 12/12/2022 R 1:10pm - 4:00pm KING W387
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 703 (01) - Teaching of Mathematics in Grades K-5

Teaching of Mathematics, K-5

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   24  
CRN: 13565
Methods of teaching mathematics at the elementary school level; uses of technology, manipulatives, models, and diagrams; developing unit and lesson plans; assessment ; instructional formats; teaching reading and writing in mathematics. Prereq: MATH 621 (or MATH 601); or permission.
Section Comments: Teaching of Mathematics in Grades K-5
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Karen Graham
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MW 4:10pm - 6:00pm KING N310
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 734 (01) - Statistical Computing

Statistical Computing

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 16673
This is a course on statistics-oriented programming and common computational methodologies used in statistics. Students will learn principles and techniques of sample-splitting, cross-validation, simulation, bootstrap, and optimization, and how to implement them in R. The students will gain experience of reading/modifying, writing and debugging code, and how to speed up computation. Prereq: MATH 738 or MATH 739.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Instructors: Qi Zhang
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 11:10am - 12:30pm KING S320
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 734 (1SY) - Statistical Computing

Statistical Computing

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 16674
This is a course on statistics-oriented programming and common computational methodologies used in statistics. Students will learn principles and techniques of sample-splitting, cross-validation, simulation, bootstrap, and optimization, and how to implement them in R. The students will gain experience of reading/modifying, writing and debugging code, and how to speed up computation. Prereq: MATH 738 or MATH 739.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Attributes: Scheduled meeting time, Online (no campus visits), EUNH
Instructors: Qi Zhang
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 11:10am - 12:30pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 737 (1ON) - Statistical Methods for Quality Improvement and Design

Stat Methods for QI & Design

Can be taken by students who are remote.
Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   60  
CRN: 12461
Six Sigma is a popular, data-focused methodology used worldwide by organizations to achieve continuous improvement of their existing processes, products and services or to design new ones. This course provides a thorough introduction to the Six Sigma principles, methods, and applications for continuous improvement (DMAIC process) and an overview of Design for Six Sigma (DFSS). Both manufacturing and non-manufacturing (transactional Six Sigma) applications are included. Emphasis is placed on the use of case studies to motivate the use of, as well as the proper application of, the Six Sigma methodology. Formal Six Sigma Green Belt certification from UNH may be attained by successfully completing TECH 696. Prereq: MATH 539,MATH 644; or permission.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Attributes: Online (no campus visits), EUNH
Instructors: Philip Ramsey
Start Date End Date Days Time Location
8/29/2022 12/12/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 739 (01) - Applied Regression Analysis

Applied Regression Analysis

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 10196
Statistical methods for the analysis of relationships between response and input variables: simple linear regression, multiple regression analysis, residual analysis and model selection, multi-collinearity, nonlinear curve fitting, categorical predictors, analysis of variance, analysis of covariance, examination of validity of underlying assumptions, logistic regression analysis. Emphasizes real applications with use of statistical software. Prereq: MATH 539 (or 644). Writing intensive.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Attributes: Writing Intensive Course
Instructors: Michelle Capozzoli
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 8:10am - 9:30am KING S320
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 739 (1SY) - Applied Regression Analysis

Applied Regression Analysis

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 14329
Statistical methods for the analysis of relationships between response and input variables: simple linear regression, multiple regression analysis, residual analysis and model selection, multi-collinearity, nonlinear curve fitting, categorical predictors, analysis of variance, analysis of covariance, examination of validity of underlying assumptions, logistic regression analysis. Emphasizes real applications with use of statistical software. Prereq: MATH 539 (or 644). Writing intensive.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Attributes: Writing Intensive Course, Scheduled meeting time, Online (no campus visits), EUNH
Instructors: Michelle Capozzoli
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 8:10am - 9:30am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 740 (1ON) - Design of Experiments I

Design of Experiments I

Can be taken by students who are remote.
Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   50  
CRN: 11573
Course in design of experiments with applications to quality improvement in industrial manufacturing, engineering research and development, or research in physical and biological sciences. Experimental factor identification, statistical analysis and modeling of experimental results, randomization and blocking, full factorial designs, random and mixed effects models, replication and sub-sampling strategies, fractional factorial designs, response surface methods, mixture designs, and screening designs. Focuses on various treatment structures for designed experimentation and the associated statistical analyses. Use of statistical software. Prereq: MATH 539 (or 644); or permission.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Attributes: Online (no campus visits), EUNH
Instructors: Philip Ramsey
Start Date End Date Days Time Location
8/29/2022 12/12/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 745 (1SY) - Foundations of Applied Mathematics I

Foundations of Applied Math

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 10844
An introduction to Partial Differential Equations (PDEs) and associated mathematical methods and the analytical foundation for applied mathematics. Topics include: PDE classification, superposition, separation of variables, orthonormal functions, completeness, convergence, Fourier Series, Sturm-Liouville eigenvalue problems, and eigenfunctions. Methods are introduced for the analysis and solution of boundary value problems, in particular, the Heat, Wave, and Laplace equations. Prereq: MATH 527 and MATH 528; or equivalent.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Attributes: Scheduled meeting time, Online (no campus visits), EUNH
Instructors: Marianna Shubov
Start Date End Date Days Time Location
8/29/2022 12/12/2022 TR 12:40pm - 2:00pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 753 (01) - Introduction to Numerical Methods I

Intro to Numerical Methods I

Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 13619
Introduces mathematical algorithms and methods of approximation. Topics include a wide survey of approximation methods. Methods examined include polynomial interpolation, root finding, numerical linear algebra, numerical integration, and the approximation of differential equations. Included in each case is a study of the accuracy and stability of a given technique, as well as its efficiency. Prereq: MATH 426; MATH 445 (or CS 410 or IAM 550).
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Instructors: John Gibson
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 12:40pm - 2:00pm KING N343