Timeroom: Fall 2022

Displaying 251 - 260 of 430 Results for: Attributes = EUNH
Law   Franklin Pierce School of Law :: Skills (LAW)

LSK 953 (1LH) - Writing for Practice

Writing for Practice

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2022 - Law (08/22/2022 - 12/16/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 15707
This course is designed to help second- and third-year students develop the kinds of writing, organization, critical thinking, editing and collaborative work skills essential to law practice and passing the bar. Students will work on multiple short (less than 5 pages) weekly assignments, engaging them in reading the law; conceptualizing, outlining, writing, editing, and revising legal documents; practicing writing concisely and clearly; researching and using samples, templates, and other practice-based resources; and working on related tasks. These assignments are designed to help students sharpen their ability to write any kind of legal document, using the appropriate format for the intended audience. The course will focus primarily on civil matters and will include some writing on criminal issues. The course's focus on essential skills, organization, analysis, doctrine, precision and conciseness, will transfer to writing in any legal setting.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Only listed majors in section: LAW: JD HYBRID
Attributes: Law Upper Level Writing
Instructors: Sophie Sparrow
Start Date End Date Days Time Location
8/22/2022 12/16/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 647 (1SY) - Complex Analysis for Applications

Complex Analysis for Applictns

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 16505
Complex numbers, analytic functions, Cauchy-Riemann equations, conformal mapping, contour integration, Cauchy's integral formula, infinite series, residue calculus, Fourier and Laplace transforms. Prereq: MATH 528. (Not offered for credit if credit is received for MATH 788.)
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Mutual Exclusion : MATH 788
Instructors: Marianna Shubov
Start Date End Date Days Time Location
8/29/2022 12/12/2022 TR 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 734 (1SY) - Statistical Computing

Statistical Computing

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
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
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

Online Course Delivery Method: Online (no campus visits), EUNH
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
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 (1SY) - Applied Regression Analysis

Applied Regression Analysis

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
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
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

Online Course Delivery Method: Online (no campus visits), EUNH
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
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

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
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
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 755 (1SY) - Probability with Applications

Probability with Applications

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2022 - Full Term (08/29/2022 - 12/12/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 14330
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. Prereq: MATH 528 and MATH 539 (or MATH 644).
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Classes not allowed in section: Freshman, Sophomore
Instructors: Linyuan Li
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MWF 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 834 (1SY) - Statistical Computing

Statistical Computing

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
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
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 (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 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.
Instructors: Qi Zhang
Start Date End Date Days Time Location
8/29/2022 12/12/2022 MW 9:40am - 11:00am ONLINE