Timeroom: Spring 2022

Displaying 311 - 320 of 460 Results for: Attributes = EUNH
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 836 (1SY) - Advanced Statistical Modeling

Advanced Statistical Modeling

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 56091
This is a course on statistical models behind normal linear model. Topics covered in this course include generalized linear model, linear mixed model, generalized additive model, generalized linear mixed model, generalized additive mixed model, and smoothing methods if time allows.
You must sign up in the Dept Office before registering through WEBCAT.
Prerequisite(s): (MATH 835 with minimum grade of B- or MATH 839 with minimum grade of B- )
Instructors: Qi Zhang
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MWF 8:10am - 9:30am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 838 (1SY) - Data Mining and Predictive Analytics

Data Mining & Pred Analytics

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 52826
An introduction to supervised and unsupervised methods for exploring large data sets and developing predictive models. Unsupervised methods include: market basket analysis, principal components, clustering, and variables clustering. Important statistical and machine learning methods (supervised learning) include: Classification and Regression Tress (CART), Random Forests, Neural Nets, Support Vector Machines, Logistic Regression and Penalized Regression. Additional topics focus on metamodeling, validation strategies, bagging and boosting to improve prediction or classification, and ensemble prediction from a set of diverse models. Required case studies and projects provide students with experience in applying these techniques and strategies. The course necessarily involves the use of statistical software and programming languages. Students must have completed a calculus-based introductory statistics course.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Philip Ramsey
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MW 12:40pm - 2:00pm 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: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 51845
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.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Philip Ramsey
Start Date End Date Days Time Location
1/25/2022 5/9/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 841 (1SY) - Survival Analysis

Survival Analysis

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 56500
Explorations of models and data-analytic methods used in medical, biological, and reliability studies. Event-time data, censored data, reliability models and methods, Kaplan-Meier estimator, proportional hazards, Poisson models, loglinear models. The use of statistical software, such as SAS, JMP, or R, is fully integrated into the course. Prereq: MATH 839. (Offered in alternate years.)
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Qi Zhang
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MWF 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 856 (1SY) - Principles of Statistical Inference

Princpls Statistical Inference

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 50584
Introduces the basic principles and methods of statistical estimation and model fitting. One- and two-sample procedures, consistency and efficiency, likelihood methods, confidence regions, significance testing, Bayesian inference, nonparametric and re-sampling methods, decision theory.
You must sign up in the Dept Office before registering through WEBCAT.
Prerequisite(s): MATH 855 with minimum grade of B-
Instructors: Linyuan Li
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MWF 11:10am - 12:30pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 946 (1SY) - Advanced Theory of Statistics II

Adv Theory of Statistics II

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 3.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 54321
Asymptotic statistical inference: consistency, asymptotic normality and efficiency. Hypothesis testing: Neyman-Pearson lemma, uniformly most powerful test, generalized likelihood ration tests, Chi squared goodness-of-fit tests, Wald tests and related confidence intervals, pivotal quantities, optimality properties. Modern likelihood methods (quasi, pseudo and composite). Algorithmic inference: Gibbs sampling, bootstrapping, simultaneous inferences in high-dimensional data and functional data. Nonparametric and semiparametric estimation methods, asymptotic estimation theory and large sample tests. Prereq: MATH 945; or permission.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Linyuan Li
Start Date End Date Days Time Location
1/25/2022 5/9/2022 TR 9:40am - 11:00am ONLINE
Durham   Paul College of Business&Econ :: Management

MGT 714 (1SY) - Organizational Leadership and Structure

Organizationl Leadrshp & Struc

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   40  
CRN: 54945
How structural characteristics in an organization (e.g., the design of roles, reporting relationships, coordinating mechanisms, communication systems, and processes, etc.) affect whether leader actions and choices enable or prevent high performance. An open systems framework is used to assess how reactions to change occurring inside and outside an organization determine whether individuals, groups, and organizations position themselves to adapt, grow and develop, or decline. Examination of individual roles in organizations. Prereq: ADMN 575.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MGT 614
Only listed campus in section: Durham
Only listed classes in section: Junior, Senior
Only listed majors in section: BUSADM:MGT
Instructors: Carole Barnett
Start Date End Date Days Time Location
1/25/2022 5/9/2022 TR 3:40pm - 5:00pm ONLINE
Durham   Paul College of Business&Econ :: Management

MGT 714 (2SY) - Organizational Leadership and Structure

Organizationl Leadrshp & Struc

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   40  
CRN: 54928
How structural characteristics in an organization (e.g., the design of roles, reporting relationships, coordinating mechanisms, communication systems, and processes, etc.) affect whether leader actions and choices enable or prevent high performance. An open systems framework is used to assess how reactions to change occurring inside and outside an organization determine whether individuals, groups, and organizations position themselves to adapt, grow and develop, or decline. Examination of individual roles in organizations. Prereq: ADMN 575.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MGT 614
Only listed campus in section: Durham
Only listed classes in section: Junior, Senior
Only listed majors in section: BUSADM:MGT
Instructors: Carole Barnett
Start Date End Date Days Time Location
1/25/2022 5/9/2022 W 5:10pm - 8:00pm ONLINE
Manchester   Liberal Arts :: Music

MUSI 405 (M1) - Survey of Music in America

Survey of Music in America

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - UNHM Credit (15 weeks) (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 53303
From colonial times to the present, including various European influences, the quest for an American style, and the emergence of such indigenous phenomena as jazz. This course does not fulfill a music major program requirement nor does it satisfy the Fine and Performing Arts Discovery requirement for any music major program. (Formerly MUSI 511).
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MUSI 511
Campuses not allowed in section: Durham
Attributes: Fine&PerformingArts(Discovery)
Instructors: David Price
Start Date End Date Days Time Location
1/25/2022 5/9/2022 M 6:01pm - 9:00pm ONLINE
Durham   Life Sciences & Agriculture :: Natural Resources

NR 606 (1SY) - International Energy Topics

International Energy Topics

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   22  
CRN: 53007
This course introduces students to international energy topics. Students will be exposed to a historical context and current status of several energy-related issues from an international perspective. Topics range from energy poverty, energy and climate change and global fossil fuel subsidies. Studies of specific technologies will be delivered through the context of international leaders, Iceland and geothermal, the UK and offshore wind and solar in Germany.
You must sign up in the Dept Office before registering through WEBCAT.
Classes not allowed in section: Freshman
Instructors: Clayton Mitchell
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MW 2:10pm - 4:00pm ONLINE