MINOR REQUIREMENTS
The Department of Statistics offers a minor in Statistics. To declare a minor in Statistics, please meet with a Faculty Advisor. You can make an appointment here. For any additional questions, please contact undergraduate@stat.tamu.edu. Note: the prerequisite for STAT 211 is MATH 152 or MATH 172.
| Lower Division Courses | ||
| STAT 211 | Principles of Statistics I | 3 |
| STAT 212 | Principles of Statistics II | 3 |
| Upper Division Electives | ||
| Select three of the following: 1 | ||
| Statistical Computing | 3 | |
| Design and Analysis of Experiments | 3 | |
| Principles of Survey Samplings | 3 | |
| Introduction to Linear Models | 3 | |
| Mathematical Statistics I | 3 | |
| Mathematical Statistics II | 3 | |
| Methods in Time Series Analysis | 3 | |
| Multivariate Analysis and Statistical Learning | 3 | |
| Bayesian Statistics | 3 | |
| Applied Biostatistics and Data Analysis | 3 | |
| Statistical Bioinformatics | 3 | |
| Categorical Data Analysis | 3 | |
| Directed Studies | 3 | |
| Special Topics in… | 3 | |
Additional Requirements:
Students must make a grade of “C” or better in all courses.
Substitutions for the minor must be approved by the Statistics Department.
StatLinks
Calendar
August 2018
New Graduate Student Orientation
August 21, 201809:00 AM / 05:00 PM Blocker Building, Room 457, 453 979-845-3141
2018 Faculty Retreat
August 24, 201808:00 AM / 04:00 PM Hilton College Station Hotel & Conference Center 979-845-3141
Departmental Colloquia: Anuj Srivastava
August 31, 201811:30 AM / 12:30 PM Blocker Building (BLOC), Room 113 979-845-3141
ANUJ SRIVASTAVA 
Department of Statistics
Florida State University
Recent Advances in Elastic Functional Data Analysis
ABSTRACT
Functional data analysis (FDA) is fast becoming an important research area, due to its broad applications in many branches of science, including biostatistics and bioinformatics. An essential component of FDA is registration of points across functional objects. Without proper registration, the results are often inferior and difficult to interpret.
The current practice in FDA community is to treat registration as a pre-processing step, using off-the-shelf alignment procedures, and follow it up with statistical analysis of the resulting data. In contrast, Elastic FDA is a more comprehensive approach, where one solves for the registration and statistical inferences in a simultaneous fashion. The key idea here is to use Riemannian metrics with appropriate invariance properties, to form objective functions for alignment and to develop statistical models involving functional data. While these elastic metrics are complicated in general, we have developed a family of square-root transformations that map these metrics into simpler Euclidean representations, thus enabling more standard statistical procedures. Specifically, we have developed techniques for elastic functional PCA and elastic regression models involving functional variables. I will demonstrate this ideas using imaging data in neuroscience and bioinformatics, where biological structures can often be represented as functions (curves or surfaces) on intervals or spheres. Examples of curves include DTI fiber tracts and chromosomes while examples of surfaces include subcortical structures (hippocampus, thalamus, putamen, etc). Statistical goals here include shape analysis and modeling of these structures and to use their shapes in medical diagnosis.
Friday, 8/31/2018, BLOC 113, 11:30 AM