Timeroom: Spring 2017

Displaying 141 - 150 of 218 Results for: Attributes = EUNH
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 740 (1BB) - Design of Experiments I

Credits: 4.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   75  
CRN: 53312
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.
Section Comments: (MATH 740.1BB) Offered 100% online.
Only listed campus in section: Durham
Classes not allowed in section: Freshman, Sophomore
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 743 (1SY) - Time Series Analysis

Credits: 4.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 56545
An introduction to univariate time series models and associated methods of data analysis and inference in the time domain and frequency domain. Topics include: auto regressive (AR), moving average (MA), ARMA and ARIMA processes, stationary and non-stationary processes, seasonal ARIMA processes, auto-correlation and partial auto-correlation functions, identification of models, estimation of parameters, diagnostic checking of fitted models, forecasting, spectral density function, periodogram and discrete Fournier transform, linear filters, parametric spectral estimation, dynamic Fournier analysis. Additional topics may include wavelets and long memory processes (FARIMA) and GARCH Models. The use of statistical software, such as JMP, or R, is fully integrated into the course. Prereq: MATH 739. Offered in alternate years in the spring semester.
Only listed campus in section: Durham
Classes not allowed in section: Freshman, Sophomore
Attributes: Scheduled meeting time, Online with some campus visits, EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 MWF 9:40am - 11:00am HEW 301
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 756 (1SY) - Principles of Statistical Inference

Princpls Statistical Inference

Credits: 4.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 50966
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. Prereq: MATH 755; or permission.
Section Comments: (MATH 756.1SY) Offered online synchronously; no campus visits required.
Only listed campus in section: Durham
Classes not allowed in section: Freshman, Sophomore
Attributes: Scheduled meeting time, Online with some campus visits, EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 MWF 11:10am - 12:30pm PARS N114
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 796 (2BB) - Top/Basic Introduction to R

Credits: 1.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 57318
New or specialized courses not covered in regular course offerings. Prereq: permission of instructor. May be repeated.
Repeat Rule: May be repeated up to unlimited times.
Only listed campus in section: Durham
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 836 (1SY) - Advanced Statistical Methods for Research

Adv Stat Methods for Research

Credits: 3.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 52179
An introduction to multivariate statistical methods, including principal components, discriminant analysis, cluster analysis, factor analysis, multidimensional scaling, and MANOVA. Additional topics include generalized linear models, general additive models, depending on the interests of class participants. This course completes a solid grounding in modern applications of statistics used in most research applications. The use of statistical software, such as JMP, S PLUS, or R, is fully integrated into the course. Prereq: MATH 835 or MATH 839.
Section Comments: (MATH 836.1SY) Offered online synchronously; no campus visits required.
Prerequisite(s): MATH 835
Attributes: Scheduled meeting time, Online with some campus visits, EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 MWF 8:10am - 9:30am MUB DL
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

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

Data Mining & Pred Analytics

Credits: 3.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 56548
An introduction to supervised and unsupervised methods for exploring large data sets and developinh 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. Prereq: MATH 539 (or MATH 644); or permission.
Attributes: Scheduled meeting time, Online with some campus visits, EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 MW 12:40pm - 2:00pm KING N129
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 840 (1BB) - Design of Experiments I

Design of Experiments I

Credits: 3.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   25  
CRN: 53313
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. Prereq: basic introductory statistics; permission.
Section Comments: (MATH 840.1BB) Offered 100% online. No campus visits required.
Prerequisite(s): MATH 836
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 843 (1SY) - Time Series Analysis

Credits: 3.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 56546
An introduction to univariate time series models and associated methods of data analysis and inference in the time domain and frequency domain. Topics include: Auto regressive (AR), moving average (MA), ARMA and ARIMA processes, stationary and non-stationary processes, seasonal ARIMA processes, auto-correlation and partial auto-correlation functions, identification of models, estimation of parameters, diagnostic checking of fitted models, forecasting, spectral density function, periodogram and discrete Fourier transform, linear filters. parametric spectral estimation, dynamic Fourier analysis. Additional topics may include wavelets and long memory processes (FARIMA) and GARCH Models. The use of statistical software, such as JMP, or R, is fully integrated in to the course. Prereq: MATH 835 or MATH 839. Offered in alternate years in the spring.
Attributes: Scheduled meeting time, Online with some campus visits, EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 MWF 9:40am - 11:00am HEW 301
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 856 (1SY) - Principles of Statistical Inference

Princpls Statistical Inference

Credits: 3.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   10  
CRN: 50967
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. Prereq: MATH 855; or permission.
Section Comments: (MATH 856.1SY) Offered online synchronously; no campus visits required.
Attributes: Scheduled meeting time, Online with some campus visits, EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 MWF 11:10am - 12:30pm PARS N114
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 896 (2BB) - Topics in Mathematics and Statistics

Top/Basic Introduction to R

Credits: 1.0
Term: Spring 2017 - Full Term (01/24/2017 - 05/08/2017)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 57319
New or specialized courses not covered in regular course offerings. Prereq: permission of instructor. May be repeated.
Repeat Rule: May be repeated for a maximum of 99 credits.
Attributes: Online (no campus visits), EUNH
Instructors: STAFF
Start Date End Date Days Time Location
1/24/2017 5/8/2017 Hours Arranged ONLINE