Date Submitted: Mon, 12 Mar 2018 20:45:10 GMT

Viewing: ST 437 / ST 537 : Applied Multivariate and Longitudinal Data Analysis

Last approved: Wed, 07 Mar 2018 16:08:04 GMT

Last edit: Wed, 07 Mar 2018 16:07:58 GMT

Changes proposed by: boos
Catalog Pages referencing this course
Change Type
Major
ST (Statistics)
437
032431
Dual-Level Course
Yes
537
Cross-listed Course
No
Applied Multivariate and Longitudinal Data Analysis
Mult. and Long. Data Analysis
College of Sciences
Statistics (17ST)
Term Offering
Spring Only
Offered Every Year
Spring 2017
Previously taught as Special Topics?
Yes
1
 
Course Prefix/NumberSemester/Term OfferedEnrollment
ST 495/ST 590Spring 2016495-4, 590-29
Course Delivery
Face-to-Face (On Campus)
Distance Education (DELTA)
Online (Internet)

Grading Method
Graded with S/U option
3
16
Contact Hours
(Per Week)
Component TypeContact Hours
Lecture3
Course Attribute(s)


If your course includes any of the following competencies, check all that apply.
University Competencies

Course Is Repeatable for Credit
No
 
 
Ana-Maria Staicu
Associate Professor
full

Open when course_delivery = campus OR course_delivery = blended OR course_delivery = flip
Enrollment ComponentPer SemesterPer SectionMultiple Sections?Comments
Lecture1010NoWe expect up to 30 in the graduate version, ST 537, in the same classroom.
Open when course_delivery = distance OR course_delivery = online OR course_delivery = remote
Delivery FormatPer SemesterPer SectionMultiple Sections?Comments
LEC1010Nograduate version online
P: ST 422 and ST 430
P: ST 512 or ST 514 or ST 515 or ST 517
Is the course required or an elective for a Curriculum?
No
An introduction to use of statistical methods for analyzing multivariate and longitudinal data collected in experiments and surveys. Topics covered include multivariate analysis of variance, discriminant analysis, principal components analysis, factor analysis, covariance modeling, and mixed effects models such as growth curves and random coefficient models. Emphasis is on use of a computer to perform statistical analysis of multivariate and longitudinal data.

The course is designed to expose students to the analysis of multivariate data (multiple variables or traits measured for the same individual) and longitudinal data (same variable or trait measured repeatedly on individuals over time). The course will be primarily focused on exposure to and practical implementation of various statistical concepts and methodology to analyze such data sets.  There were previously two courses covering this material: ST 731 Applied Multivariate Statistics Analysis and ST 732 Longitudinal Data Analysis.  We decided to combine these two courses in order for students to get some of both courses in one course.  A new course proposal will be submitted in the future to make ST 732 a PhD level course.  There are no plans for ST 731.


No

Is this a GEP Course?
No
GEP Categories

Humanities Open when gep_category = HUM
Each course in the Humanities category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Mathematical Sciences Open when gep_category = MATH
Each course in the Mathematial Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Natural Sciences Open when gep_category = NATSCI
Each course in the Natural Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

Social Sciences Open when gep_category = SOCSCI
Each course in the Social Sciences category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Interdisciplinary Perspectives Open when gep_category = INTERDISC
Each course in the Interdisciplinary Perspectives category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Visual & Performing Arts Open when gep_category = VPA
Each course in the Visual and Performing Arts category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
 

 
 

Health and Exercise Studies Open when gep_category = HES
Each course in the Health and Exercise Studies category of the General Education Program will provide instruction and guidance that help students to:
 
 

 
 

 
 

 
 

 
&
 

 
 

 
 

 
 

Global Knowledge Open when gep_category = GLOBAL
Each course in the Global Knowledge category of the General Education Program will provide instruction and guidance that help students to achieve objective #1 plus at least one of objectives 2, 3, and 4:
 
 

 
 

 
Please complete at least 1 of the following student objectives.
 

 
 

 
 

 
 

 
 

 
 

US Diversity Open when gep_category = USDIV
Each course in the US Diversity category of the General Education Program will provide instruction and guidance that help students to achieve at least 2 of the following objectives:
Please complete at least 2 of the following student objectives.
 
 

 
 

 
 

 
 

 
 

 
 

 
 

 
 

Requisites and Scheduling
 
a. If seats are restricted, describe the restrictions being applied.
 

 
b. Is this restriction listed in the course catalog description for the course?
 

 
List all course pre-requisites, co-requisites, and restrictive statements (ex: Jr standing; Chemistry majors only). If none, state none.
 

 
List any discipline specific background or skills that a student is expected to have prior to taking this course. If none, state none. (ex: ability to analyze historical text; prepare a lesson plan)
 

Additional Information
Complete the following 3 questions or attach a syllabus that includes this information. If a 400-level or dual level course, a syllabus is required.
 
Title and author of any required text or publications.
 

 
Major topics to be covered and required readings including laboratory and studio topics.
 

 
List any required field trips, out of class activities, and/or guest speakers.
 

Dr. Staicu will teach the course as part of her standard teaching obligation, thus no new resources are required.

Students will gain a basic competency in statistical analysis of multivariate and longitudinal data sets. They will be able to use SAS or R to carry out these analyses. Students will learn to interpret the output from these programs and be able to integrate those results into their research publications.


Student Learning Outcomes

By the end of the course, the students will be able to:


(1) select, carry out, and interpret appropriate statistical methods for describing and analyzing multivariate/longitudinal data sets in the context of their own research interests; (2) explain a full range of multivariate/longitudinal data analysis methods and their use and limitations in a research context, and (3) examine critically their own and other researchers use of methods of analysis for multivariate and longitudinal data.


ST 537 Only: Demonstrate the ability to work with more theoretical aspects of selected topics via derivations, proofs, or other more advanced statistical techniques 


Evaluation MethodWeighting/Points for EachDetails
Homework40%537 students will have additional HW problems that address the additional learning outcomes for graduate students.
Midterm30%Closed book, closed notes. ST 537 students will have additional Exam questions that address the additional learning outcomes for graduate students.
Final Exam30%Closed book, closed notes. ST 537 students will have additional Exam questions that address the additional learning outcomes for graduate students.
TopicTime Devoted to Each TopicActivity
Introduction to Basic Concepts2 weeks(a) Examples of a few multivariate and longitudinal data sets
(b) Review of vectors and matrices
(c) Review of common distributions
(d) Review of common summary statistics
(e) Basic regression models
Inference about mean vectors2 weeksInference about mean vectors
i. Inference about a single mean vector (Hotelling's T^2, Likelihood ratio test, simultaneous confidence intervals)
ii. Inference about multiple mean vectors (paired comparison, repeated measured design, MANOVA, profile analysis)
Principal Components Analysis1 weekPrincipal Components Analysis
Factor Analysis3 weeksFactor analysis
i. Orthogonal factor model and estimation (PCA based method, likelihood based method) ii. Factor rotation and factor scores
iii. Classification and clustering
In class examination
General Linear Models2 weeksGeneral Linear Models
i. Parametric mean model
ii. Models for covariance
iii. Inference by maximum likelihood iv. Restricted maximum likelihood
Linear Mixed models2 weeksLinear Mixed models
i. Growth curves
ii. Random coefficient model. Estimation of regression and covariance parameters iii. Linear mixed effects model. Estimation, inference, and prediction
Generalized linear mixed models3 weeksGeneralized Linear Mixed Models
i. Marginal models (generalized estimating equations). Estimation and inference for regression parameters.
ii. Generalized linear mixed models. Estimation and inference.
Final Exam1 week
ST 437 and 537 will differ in the following way. 537 will have an additional learning outcome: Demonstrate the ability to work with more theoretical aspects of selected topics via derivations, proofs, or other more advanced statistical techniques. 537 students will have additional HW and Exam questions to evaluate this learning outcome.

mlnosbis 1/10/2017: No overlapping courses outside of ST, no consultation required. 1) Expand justification to address how this differs from ST 731 and 732. 2) Has this been previously taught as special topics? What are the previous enrollment numbers?

ABGS Reviewer Comments:
-Do we want additional detail about the additional homework and additional exam questions for the 500-level? It seems that in the past we have asked for clearer articulation.

pjharrie 1/31/2017 I think the more clearly the differences between 400/500 levels are articulated, the better. So, I feel that the ABGS Reviewer comments should be addressed.
muse (Tue, 04 Aug 2015 16:49:11 GMT): This should be marked as a Dual-Level Course
gmneugeb (Tue, 29 Sep 2015 18:47:17 GMT): Rollback: .
gmneugeb (Tue, 29 Sep 2015 19:19:21 GMT): Rollback: .
lamarcus (Fri, 05 Feb 2016 21:42:39 GMT): Rollback: Rolled back at instructor request
allloyd (Mon, 21 Nov 2016 15:38:55 GMT): Passed college committee 11/11/16
Key: 7238