Timeroom: Fall 2021

Displaying 301 - 310 of 488 Results for: Attributes = EUNH
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 759 (1ON) - Introduction to the R Software

Introduction to the R Software

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 1.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Credit/Fail Grading
Class Size:   30  
CRN: 13712
This course provides a basic introduction to the open-sources statistical software R for students who have never used this software or have never formally learned the basics of it. Topics include: Numeric calculations, simple and advanced graphics, object management and work-flow, RStudio, user-contributed packages, basic programming, writing of functions, statistical modeling and related graphs, distributed computing, reproducible research and document production via markup language. Cr/F.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Ernst Linder
Start Date End Date Days Time Location
8/30/2021 12/13/2021 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 796 (1SY) - Topics

Topics

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 16891
New or specialized courses not covered in regular course offerings. Prereq: permission of instructor.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated up to unlimited times.
Instructors: Qi Zhang
Start Date End Date Days Time Location
8/30/2021 12/13/2021 MW 9:40am - 11:00am ONLINE
Additional Course Details: 

Topic: Statistical Computing

This course introduces common methods for numerical analysis and optimization for statistical problems, general Monte Carlo simulations, MCMC basics, and resampling methods, and exposes the students to intermdiate to advanced topics in R programming and data science practice, such as writing functions, data structure, Rcpp, prinicples of visualization, and methods of performance evaluation.

Co-req: MATH 739/839, 738/838 or equivalent, and some background in R programming and linear algebra

Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 797 (2SY) - Senior Seminar

Senior Seminar

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 14085
Exploration of mathematical topics beyond the student's previous coursework in the seminar format. The course focus is on independent research, collaborative work and classroom engagement; oral presentations and written work are required. Prereq: senior standing.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Equivalent(s): MATH 698
Only listed majors in section: AM:COMPUT, AM:DYNCNT, AM:ECON, AM:FLUIDDYN, AM:SOLMECH, MATH (BA), MATH (BS), STATISTICS
Instructors: Marianna Shubov
Start Date End Date Days Time Location
8/30/2021 12/13/2021 TR 2:10pm - 3:30pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 835 (1SY) - Statistical Methods for Research

Statistical Mthds for Research

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   17  
CRN: 15227
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.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Linyuan Li
Start Date End Date Days Time Location
8/30/2021 12/13/2021 MW 11:10am - 12:30pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

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

Stat Methods for QI & Design

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 12744
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.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Philip Ramsey
Start Date End Date Days Time Location
8/30/2021 12/13/2021 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 839 (1SY) - Applied Regression Analysis

Applied Regression Analysis

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 15228
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.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Michelle Capozzoli
Start Date End Date Days Time Location
8/30/2021 12/13/2021 MWF 8:10am - 9:30am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 840 (1ON) - Design of Experiments I

Design of Experiments I

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 11739
First 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. Students must have completed an introductory statistics course.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Philip Ramsey
Start Date End Date Days Time Location
8/30/2021 12/13/2021 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 845 (1SY) - Foundations of Applied Mathematics I

Foundations of Applied Math

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 10945
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. Students are required to have a mastery of differential equations and ordinary differential equations.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Marianna Shubov
Start Date End Date Days Time Location
8/30/2021 12/13/2021 TR 12:40pm - 2:00pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 855 (1SY) - Probability with Applications

Probability with Applications

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 15229
Introduces the theory, methods, and applications of randomness and random processes. Probability concepts, random variable, expectation, discrete and continuous probability distributions, joint distributions, conditional distributions; moment-generating functions, convergence of random variables.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Ernst Linder
Start Date End Date Days Time Location
8/30/2021 12/13/2021 MWF 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 859 (1ON) - Introduction to the R software

Introduction to the R software

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 1.0
Term: Fall 2021 - Full Term (08/30/2021 - 12/13/2021)
Grade Mode: Graduate Credit/Fail grading
Class Size:   15  
CRN: 13713
This course provides a basic introduction to the open-sources statistical software R for students who have never used this software or have never formally learned the basics of it. Topics include: Numeric calculations, simple and advanced graphics, object management and work-flow, RStudio, user-contributed packages, basic programming, writing of functions, statistical modeling and related graphs, distributed computing, reproducible research and document production via markup language. Cr/F.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: Ernst Linder
Start Date End Date Days Time Location
8/30/2021 12/13/2021 Hours Arranged ONLINE