[Cowystats] CO/WY ASA: DU Seminar and Gertrude Cox scholarship

[Matt Pocernich]

## Gertrude Cox Scholarship
## Feb 28  Tom Hamill (NOAA) Improving Probabilistic Weather Forecasts
## Mar 9   University of Denver - data mining and geospatial statistics.
## Mar 28  UCHSC Biometrics seminar (noon) 

## Apr 20  CO/ WY Spring meeting
## Apr 27  Seminar Colorado School of Mines (tentative)
## 

This note is mainly to provide details on the seminar at DU March 9th
as well to share information about the Gertrude Cox Scholarship.  Also
note that you can view past notes at the chapter website.
http://www.stat.colostate.edu/ASA/


Thanks,

Matt

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The American Statistical Association (ASA) would like to announce the
2007 Gertrude Cox Scholarship.  The Gertrude Cox Scholarship is awarded
each year to encourage women to enter statistically oriented
professions.  The ASA Committee on Women in Statistics and the Caucus
for Women in Statistics sponsor the scholarship.

Application is limited to women who are citizens or permanent residents
of the United States or Canada, and who are admitted to full-time study
in a graduate statistical program by July 1 of the award year.  Women
entering or in the early stages of graduate training (M.S. or Ph.D.) are
especially encouraged to apply.

More information is available at 

http://www.amstat.org/awards/index.cfm?fuseaction=cox-scholarship


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Wednesday February 28th - 4pm 

Improving Probabilistic Weather Forecasts

Thomas M. Hamill
NOAA Earth System Research Lab, Physical Sciences Division
Boulder, CO

Metro State College Denver 
Jointly sponsored by Metro Department of Meteorology, Metro Department of Statistics and CO/WY ASA. 
Refreshments provided.

In the Science Building Room 103  Metro State College Denver
See  http://www.mscd.edu/enroll/admissions/campus/map/ for a campus
and parking information.  Note that the campus is very well served by
RTD light rail lines.

Abstract ***

Weather forecasts, we all know, inevitably have errors, sometimes small,
sometimes large. There are two main sources of errors in numerical
weather predictions.  The first is "chaos," or the sensitive dependence
on the initial condition.  Any small error in the initial description of
the weather will tend to grow larger and larger as the forecast lead
increases, though the error growth rate may vary from one day to the
next.  The other source of error is imperfections in the numerical model
used to make the weather forecast.

While the current practice is to issue deterministic forecasts ("high of
60 today") a more intellectually honest way of communicating the
forecast is to do so probabilistically, indicating in some fashion the
uncertainty in the forecast.
In this talk we will demonstrate how a long time series of past
forecasts, which we call "reforecasts" and associated weather
observations can be used to generate skillful, reliable probabilistic
forecasts, forecasts that account for the uncertainty due to chaos,
forecasts that statistically adjust for many of the systematic errors
introduced by the forecast model.  We'll show that a statistically
adjusted weather forecast is much more skillful than a forecast without
this statistical adjustment.

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University of Denver/ Colorado/ Wyoming Chapter of the ASA Seminar.

Hosted by the Department of Statistics and Operations Technology
University of Denver

Room 240
Daniels College of Business
University of Denver

Friday March 9th  2:00 - 4:30

Emma Vazirabadi
Director of Workforce Analytics
AIMCO

Targeting and Saving High Value Employees:  A priceless HR Concept

Apartment Investment and Management Company (AIMCO) is the nation's
largest owner and operator of apartment communities, with nearly 1,370
communities that include approximately 240,000 units.
AIMCO Human Resources with more than 60 employees and six internal
departments is a structured department within in the organization that
strives for recruiting employees from the best employee markets, and
providing competitive compensation and benefits.    

The use of various data mining approaches as it pertains to HR modeling
is multi faceted. However, the SPSS predictive modeling solution,
Clementine, will allow us reduce recruiting costs substantially by
implementing a Candidate Profiling predictive modeling system that uses
our current employee data (demographic, resume data, performance review
data) to profile our best performers and score their data against new
candidate to predict best performers for particular job description.
This essentially empowers the AIMCO Talent team with the ability to only
target and hire the right candidates, and in turn optimize resources,
reduce employee turnover and minimize recruiting costs


Tim Coburn
School of Information Technology and Computing
Abilene Christian University

A local-spatial prediction approach for estimating the volumes of
recoverable unconventional natural gas

This presentation describes an algorithmic approach to estimating the
volume of recoverable, unconventional natural gas that combines features
of cross-validation with the jackknife and bootstrap procedures. The
procedure yields estimated volumes of gas at individual untested
drilling sites as well as regional estimates that can be used in
economic assessments. Simulation experiments using known data from the
Michigan Basin indicate that the estimated total recoverable volume is
within four percent of the observed amount. The algorithm provides a
reasonable alternative to geostatistical approaches which require more
direct knowledge of the spatial trend in the subsurface.

This work is sponsored by the Eastern Energy Resources Division of the
U.S. Geological Survey, which is responsible for producing estimates of
the remaining energy resources used to support the strategic initiatives
of various governmental agencies.



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### Keith A. Baggerly from the University of Texas M. D. Anderson
Cancer Center Thurs March 29th: Preventive Medicine and Biometrics
Seminar 12-1pm CPH Auditorium 1J05, 9th St Campus, UCHSC sponsored
with the Bioinformatics Department at the University of Colorado
Health Science Center. (Abstract to follow) 



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Spring Meeting Friday April 20th - NCAR Mesa Lab - beautiful
weather guaranteed. In addition to several invited speakers, we
strongly encourage students to present their research. Keep in mind
the meeting is a friendly environment in which to let the local
statistics community know what you have been working on the the last n
years. More details to follow. 




-- 
Matt Pocernich
National Center for Atmospheric Research
Research Applications Laboratory
(303) 497-8312