Timeroom: Fall 2022

Displaying 121 - 130 of 153 Results for: Subject = MATH
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 799 (01) - Senior Thesis

Senior Thesis

Credits: 2.0 or 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 10891
Students work under the direction of a faculty sponsor to plan and carry out independent research resulting in a written thesis. Required for honors-in-major. Prereq: senior standing; a written proposal endorsed by a faculty sponsor and approved by the department chairperson (or designee).
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 4 credits.
Attributes: Writing Intensive Course
Instructors: Karen Graham
Start Date End Date Days Time Location
8/29/2022 12/12/2022 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 801 (01) - Exploring Mathematics for Teachers I

Exploring Math for Teachers I

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 12475
Provides prospective elementary teachers with the opportunity to explore and master concepts involving number systems and operations, data analysis and probability. Additional topics may include geometry, measurement, and algebraic thinking. Mathematical reasoning, problem solving, and the use of appropriate manipulatives and technology are integrated throughout the course. Readings, class discussions, and assignments focus on mathematics content as well as applicable theories of learning, curriculum resources, and state and national recommendations. The course models instructional techniques that can be adapted to the elementary curricula. Credit offered only to M.Ed. and M.A.T., certificate students, and in-service teachers. (Not offered for credit if credit is received for MATH 821 or MATH 823.)
Section Comments: This course is not offered for credit to CEPS majors.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): (EDUC 500 or EDUC 935 with minimum grade of B- )
Equivalent(s): MATH 601, MATH 821, MATH 823
Instructors: Sheree Sharpe
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MW 2:10pm - 4:00pm KING N310
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 805 (01) - Introduction to Mathematics and Statistics Teaching

Intro to Math Stat Teaching

Credits: 1.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Graduate Credit/Fail grading
Class Size:   10  
CRN: 16898
This course introduces new graduate teaching assistants in mathematics and statistics to teaching in mathematics and statistics. Topics include group facilitation, active learning, grading, diversity and inclusion in the classroom, goal setting, classroom management, time management, designing rich mathematical tasks, and research on student learning.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 2 credits.
Only listed majors in section: MATH STATISTICS, MATHEMATICS, MATHEMATICS ED
Instructors: Lauren Sager
Start Date End Date Days Time Location
8/29/2022 12/12/2022 Hours Arranged TBA
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 831 (01) - Mathematics for Geodesy

Mathematics for Geodesy

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 12007
A survey of topics from undergraduate mathematics designed for graduate students in engineering and science interested in applications to geodesy and Earth Sciences. Topics include essential elements from analytic geometry, geometry of surfaces, linear algebra and statistics, Fourier analysis, discrete Fourier transforms and software, filtering applications to tidal data.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): (MATH 645 or MATH 645H or MATH 762 or MATH 862 with minimum grade of B- )
Majors not allowed in section: MATH APP, MATH:APPLIED, MATH:STATISTICS, MATHEMATICS, MATHEMATICS, MATHEMATICS, MATHEMATICS ED
Instructors: Stephen Wineberg
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 12:10pm - 1:00pm CHASE 130
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 834 (01) - Statistical Computing

Statistical Computing

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 16321
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 835 or MATH 838 or MATH 839
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 834 (1SY) - Statistical Computing

Statistical Computing

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 16322
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 835 or MATH 838 or MATH 839
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 835 (01) - Statistical Methods for Research

Statistical Mthds for Research

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   18  
CRN: 10674
This course provides a solid grounding in modern applications of statistics to a wide range of disciplines by providing an overview of the fundamental concepts of statistical inference and analysis, including t-tests and confidence intervals. Additional topics include: ANOVA, multiple linear regression, analysis of cross classified categorical data, logistic regression, nonparametric statistics and data mining using CART. The use of statistical software, such as JMP. S PLUS, or R, is fully integrated into the course.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Qi Zhang
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MW 9:40am - 11:00am HAALND 104
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 835 (1SY) - Statistical Methods for Research

Statistical Mthds for Research

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   17  
CRN: 14331
This course provides a solid grounding in modern applications of statistics to a wide range of disciplines by providing an overview of the fundamental concepts of statistical inference and analysis, including t-tests and confidence intervals. Additional topics include: ANOVA, multiple linear regression, analysis of cross classified categorical data, logistic regression, nonparametric statistics and data mining using CART. The use of statistical software, such as JMP. S PLUS, or R, is fully integrated into the course.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
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 MW 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 837 (1ON) - Statistical Methods for Quality Improvement and Design

Stat Methods for QI & Design

Can be taken by students who are remote.
Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 12462
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 will be 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. Students must have completed a calculus-based introductory statistics course.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
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 839 (01) - Applied Regression Analysis

Applied Regression Analysis

Credits: 3.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 10244
Statistical methods for the analysis of relationships between response and input variables: simple linear regression, multiple regression analysis, residual analysis model selection, multi-collinearity, nonlinear curve fitting, categorical predictors, introduction to analysis of variance, analysis of covariance, examination of validity of underlying assumptions, logistic regression analysis. Emphasizes real applications with use of statistical software. Students must have completed an introductory statistics course.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Michelle Capozzoli
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 8:10am - 9:30am KING S320