| Dates | Topic | Sponsor | Cost |
|---|---|---|---|
|
June 3-July 21, 2013 |
STAT 501: Introduction to SAS Programming |
Department of Statistics George Mason University |
$500 for continuing education 1 graduate credit See website for details |
|
June 3-July 21, 2013 |
STAT 506: Introduction to SPSS |
Department of Statistics George Mason University |
$500 for continuing education 1 graduate credit See website for details |
|
June 3-July 21, 2013 |
STAT 505: Introduction to R |
Department of Statistics George Mason University |
$500 for continuing education 1 graduate credit See website for details |
|
September 24-25, 2013 |
Balancing Data Confidentiality and Data Quality |
JPSM |
$600 for JPSM affiliates $600 for full-time students $810 for others |
|
October 3-4, 2013 |
Statistical Analysis with Missing Data |
JPSM |
$600 for JPSM affiliates $600 for full-time students $810 for others |
|
November 4-5, 2013 |
Creating and Updating Price Indexes: Theory and Practice |
JPSM |
$600 for JPSM affiliates $600 for full-time students $810 for others |
|
December 11-12, 2013 |
Introduction to Survey Sampling |
JPSM |
$600 for JPSM affiliates $600 for full-time students $810 for others |
|
The course will follow the recently published book by Noel Cressie and Chris Wikle, Statistics for Spatial Data (Hoboken NJ: John Wiley and Sons, 2011). Professor Cressie will present state-of- the-art methods for spatio-temporal processes, bridging classic techniques with modern hierarchical statistical modeling concepts. From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. The course will consider a systematic approach to key quantitative techniques for the analysis of such data, particularly hierarchical (empirical and Bayesian) statistical modeling with an emphasis on dynamical spatio-temporal models. Illustrative real-world examples will be presented throughout the course. The course is composed of four subsections:
Instructor: Dr. Noel Cressie, Distinguished Professor at the National Institute for Applied Statistics Research Australia (University of Wollongong, Australia) is the instructor. He has published extensively in the areas of statistical modeling, analysis of spatial and spatio- temporal data, and empirical-Bayesian and Bayesian methods.
Location: Census Bureau Headquarters, Suitland MD, Conference Room 4 (Suitland Metro stop). All visitors should enter through Gate 7 (Metro entrance) that morning. Breakfast and lunch is available at the Census Bureau cafeteria.
Note: Attendees should have at least a Master’s level background in probability and statistical inference, and they should have a good understanding of matrix algebra.
Registration: Contact Sandra Heineck (Sandra.L.Heineck@census.gov) to reserve a place (up to 50 students can be accommodated). Any non-citizens desiring to attend should also contact Eugene Vandrovec directly at 301.763.6418 at least a week in advance.