Timeroom: Fall 2023

Displaying 511 - 520 of 800 Results for: Attributes = EUNH
Law   Franklin Pierce School of Law :: Skills (LAW)

LSK 924 (1LH) - Negotiations Workshop

Negotiations: Tech Transfer

Online Course Delivery Method: Immersion Attendance Required, Online with some campus visits, EUNH
Credits: 2.0
Term: Fall 2023 - Law Hybrid (08/16/2023 - 12/15/2023)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 14901
In this interactive workshop, students will identify and learn different theories and types of negotiations. Negotiating effectively is important in any profession, but it is critical for attorneys to sharpen and hone these skills for the benefit of clients. Negotiations occur at all levels of an attorney's practice, whether that practice is in a small firm environment, in litigation, in a corporate setting, or working with a governmental entity. Students will apply their negotiation skills to a variety of situations. Class time will be divided between discussion of selected readings, interactive negotiations, and guest attorneys who will discuss some of their own negotiated agreements. Class attendance and participation is mandatory Course enrollment is typically limited due to the nature of simulations.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Repeat Rule: May be repeated for a maximum of 6 credits.
Only listed majors in section: LAW: JD HYBRID
Attributes: Law Experiential Learning
Instructors: Marc Tejtel
Start Date End Date Days Time Location
8/16/2023 12/15/2023 Hours Arranged ONLINE
10/13/2023 10/16/2023 MFSU 8:00am - 5:00pm TBD TBD
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 2023 - Law (08/21/2023 - 12/15/2023)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 14313
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Only listed majors in section: LAW: JD HYBRID
Attributes: Law Upper Level Writing, Law Experiential Learning
Instructors: Heather Ward
Start Date End Date Days Time Location
8/21/2023 12/15/2023 Hours Arranged ONLINE
Law   Franklin Pierce School of Law :: Skills (LAW)

LSK 953 (2LH) - Writing for Practice

Writing for Practice

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 3.0
Term: Fall 2023 - Law Hybrid (08/16/2023 - 12/15/2023)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 16896
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Attributes: Law Upper Level Writing, Law Experiential Learning
Instructors: Kelsey Klementowicz
Start Date End Date Days Time Location
8/16/2023 12/15/2023 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 647 (01) - 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 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 15941
Complex numbers, analytic functions, Cauchy-Riemann equations, conformal mapping, contour integration, Cauchy's integral formula, infinite series, residue calculus, Fourier and Laplace transforms. (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.
Prerequisite(s): MATH 528
Mutual Exclusion : MATH 788
Instructors: Marianna Shubov
Start Date End Date Days Time Location
8/28/2023 12/11/2023 TR 9:40am - 11:00am ONLINE
Final Exam 12/13/2023 12/13/2023 W 10:30am - 12:30pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 734 (02) - Statistical Computing

Statistical Computing

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 14966
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 738 or MATH 739
Cross listed with : MATH 834.02
Classes not allowed in section: Freshman, Sophomore
Instructors: Qi Zhang
Start Date End Date Days Time Location
8/28/2023 12/11/2023 MWF 8:10am - 9:30am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 737 (01) - Statistical Methods for Quality Improvement and Design

Stat Methods for QI & Design

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 15996
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 539 or MATH 644
Cross listed with : MATH 837.01
Classes not allowed in section: Freshman, Sophomore
Instructors: Philip Ramsey
Start Date End Date Days Time Location
8/28/2023 12/11/2023 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 739 (02) - Applied Regression Analysis

Applied Regression Analysis

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 13534
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 539 or MATH 644
Cross listed with : MATH 839.02
Classes not allowed in section: Freshman, Sophomore
Attributes: Writing Intensive Course
Instructors: Pei Geng
Start Date End Date Days Time Location
8/28/2023 12/11/2023 MWF 8:10am - 9:30am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 740 (01) - Design of Experiments I

Design of Experiments I

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   50  
CRN: 11383
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 539 or MATH 644
Cross listed with : MATH 840.01
Classes not allowed in section: Freshman, Sophomore
Instructors: Michelle Capozzoli
Start Date End Date Days Time Location
8/28/2023 12/11/2023 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 745 (01) - 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 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 10742
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 527 and MATH 528
Cross listed with : MATH 845.01
Classes not allowed in section: Freshman, Sophomore
Instructors: Marianna Shubov
Start Date End Date Days Time Location
8/28/2023 12/11/2023 TR 12:40pm - 2:00pm ONLINE
Final Exam 12/14/2023 12/14/2023 R 1:00pm - 3:00pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 755 (02) - Probability with Applications

Probability with Applications

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Fall 2023 - Full Term (08/28/2023 - 12/11/2023)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 13535
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Prerequisite(s): MATH 528 and (MATH 539 or MATH 644)
Cross listed with : MATH 855.02
Classes not allowed in section: Freshman, Sophomore
Instructors: Linyuan Li
Start Date End Date Days Time Location
8/28/2023 12/11/2023 MWF 9:40am - 11:00am ONLINE
Final Exam 12/18/2023 12/18/2023 M 8:00am - 10:00am ONLINE