 |
WSS NEWS
|
Contents:
I want to point out two important events that will occur during June. On Friday June 4th, the Presidential Invited Session will be a talk by Andrew Kohut, Director of the Pew Research Center for The People and The Press. You may recognize him from being a regular commentator on All Things Considered, The News Hour with Jim Lehrer, or in the New York Times. Andy Kohut is also past President of AAPOR and of the Gallup Organization. His talk should be very enjoyable, and will be followed by a reception at the Union Station Grill to which all attendees are invited. The session is at a special time, 3:00 on Friday afternoon, so come and enjoy the talk and the company of your fellow WSS members. More details on the session can be found inside.
Tuesday evening, June 15th, will be the WSS Annual Dinner at Maggiano's Little Italy restaurant in Friendship Heights. Our guest speaker, and recipient of the second annual Gertrude M. Cox award, will be Prof. Alan Zaslavsky of Harvard University. Alan is an excellent speaker who regularly advised the Federal government on statistical methods. His talk will be "Tracking health care quality across space and time: Why we like really big surveys". The annual dinner is always a lot of fun, with time to share a relaxed drink and food with your friends. The winners of our annual elections and other awards will also be announced. I look forward to seeing you at both events.
Also, don't forget that the June meeting of the WSS Board of Directors is always open to any member who would like to attend. It will be 12:30-2:00 on Tuesday June 29th, in the BLS Conference Center.
Thank you,
David Marker
The WSS Annual Dinner will be held Tuesday, June 15, at Maggiano's Little Italy Restaurant located on Wisconsin Avenue in Washington, DC across the street from the Mazza Gallerie. Please see the flyer (pdf) for details and a reservation form.
This is a great opportunity to join with friends, meet colleagues, and make new acquaintances!
All are invited. We look forward to seeing you there!
Speaker: Dr. Alan Zaslavsky, Professor of Health Care Policy (Statistics) at the Harvard University Medical School. Dr. Zaslavsky is the second annual recipient of the Gertrude M. Cox Statistics Award, which recognizes a statistician making significant contributions to statistical practice. The award is made possible by funding from RTI International.
Tuesday, June 15, 2004 -- 5:30 to 8:30 pm
Maggiano's Little Italy
533 Wisconsin Ave, N.W.
202-966-5500
Red Line Friendship Heights
Validated rates for the Chevy Chase Pavilion parking garage
Dinner Includes: Mozzarella Marinara, Parmesan Garlic Bread, Spinach and Italian Salads, Four Cheese Ravioli, Chicken and Spinach Manicotti, Chicken Marsala, Lemon & Herbs Salmon, Tiramisu, and Fresh Fruit Plate, Coffee, and Tea, Tax and, Tip
Cash Bar
Must be received by Friday June 11, 2004. $42.00 per person. Make check payable to WSS.
E-mail Jeri at Jmulrow@nsf.gov or call at 703-292-4784 with questions.
Mail to: Jeri Mulrow, 1061 N. George Mason Dr., Arlington, VA 22205
WSS presented awards to 52 Washington area students at five regional science fairs this spring (District of Columbia, Fairfax County, Montgomery County, Northern Virginia, Prince George's County). Since 1986, WSS has been recognizing students whose projects demonstrate excellence in the application of statistical methods. Since 1996, The Gallup Organization has made an annual donation of $1000 for prizes. This year, a total of $550 was divided among 6 first place winners (prizes ranged between $50 and $150) and the balance will be used to purchase ASA school memberships for the winners' schools. There were 9 second place winners and each received a copy of Statistics: A Guide to the Unknown, by Tanur, et al. All first and second place winners will also receive a one-year subscription to STATS magazine. Others received certificates of honorable mention.
The judging was coordinated by Lee Abramson. Thanks to all WSS members who volunteered as judges. They are: Dwight Brock*, Gene Burns, Promod Chandhook, Bill Cleveland, Bob Clickner*, David Des Jardins, Bin Duan, Brenda Edwards, Mike Fay, Gloria Gridley, Gene Heyman, Donsig Jang, Tzu-Cheg Kao, Jurate Landwehr, Lou Mariano, Michael Messner, Stephen Miller, Steve Miller, Arnold Reznek, John Rogers, Fritz Scheuren*, Sid Schwartz, Stuart Scott*, Mike Stoto, Glenn White* and David Whitford.
* Chief Judge
The Jeanne E. Griffith Award Committee is pleased to announce that this year's award has been given to Beth A. Kilss, Supervisory Statistician and Chief, Statistical Data Section, Special Studies Branch of the Statistics of Income Division of the Internal Revenue Service.
Beth's accomplishments, which are extensive, numerous, deep and thoughtful, include:
The award ceremony honoring Beth Kilss will take place on June 16, 2004 at 4:00 in the Conference Center at the Bureau of Labor Statistics (BLS). Refreshments will be served. If you are planning to attend, kindly contact Ed Spar at copafs@aol.com so that your name can be added to the security list. BLS is located just across the street from Union Station in the Postal Square Building.
The Statistics Department at The George Washington University will offer the following Graduate Course in Fall 2004 (September 1 December 22, 2004). Enhance your statistical analysis skills by taking one or more of these courses. Registering as a non-degree student is easy - please visit www.gwu.edu/~regweb/ and click on 'Non-Degree Registration Information' for all relevant information. For questions or further information please contact Dr. Tapan Nayak, e-mail: tapan@gwu.edu, ph: 202-994-6888.
Statistics 201. Mathematical Statistics
Thursday, 6:10pm-8:40p.
Instructor: Dr. K. Ghosh
This is the first part of a two-part graduate level series in Mathematical Statistics. The objective of the course is to introduce students to the concepts of probability that are useful for understanding statistical theory (the course continues on to Stat 202 in Spring, which deals with the theory of statistical inference). Topics to be covered in Stat 201 include basics of probability theory (including conditional probability, Bayes theorem, random variables, density and mass functions), univariate transformations, expected values, moment generating functions, common probability distributions (including binomial, normal, uniform), multivariate distributions and transformations, covariance, inequalities and sampling distributions. This is roughly chapters 1 through 5 of the text: Statistical Inference (2nd Ed.) by Casella, G. and Berger, R. L.; Duxbury Press, CA.
Statistics 215. Applied Multivariate Analysis
Tuesday, 6:10pm-8:40pm
Instructor: Dr. R. Modarres
This course is intended for students interested in statistical analysis of several variables, most likely dependent, following a joint normal distribution. It covers inferential and descriptive multivariate techniques, including the multivariate normal distribution, assessing the assumption of normality, transformations to near normality, Hotelling test for the mean vector, confidence regions and simultaneous comparisons of component means, missing observations and the EM algorithm, comparisons of several multivariate means, one and two-way MANOVA, profile and principal components analysis
Statistics 217. Design of Experiments
Wednesday, 6:10pm-8:40pm
Instructor: Dr. E. Bura
This course is a graduate level introduction to Design of Experiments, an area of statistics concerned with the planning of scientific investigation. The main components of an experimental design are the selection of the independent and dependent variables to be studied, determination of sample size, and allocation of experimental units to experimental treatments.
Statistics 225. Fundamentals of Biostatistics
Thursday, 6:10pm-8:40pm
Instructor: Dr. Y. Lai
This course provides a review of the core biostatistical methods for asymptotically efficient tests and estimates of relative risks and odds ratios from prospective and retrospective, matched and unmatched studies.
Stat 227. Survival Analysis
Wednesday, 6:10pm-8:40pm
Instructor: Dr. Ping Hu
This course will discuss parametric and nonparametric methods for the analyses of events observed in time (survival data). Topics include: survival distributions, Kaplan-Meier estimate of survival functions, Greenwood's formula, Mantel-Haenszel test, logrank and generalized logrank tests, Cox proportional hazards model, parametric regression models, and power and sample size calculations for survival analysis.
Stat 257. Probability
Wednesday, 6:10pm-8:40pm
Instructor: Dr. S. Balaji
This course will discuss rigorous modern measure-theoretic probability. No prior knowledge of measure theory is assumed; the necessary concepts will be developed as necessary. Topics to be covered include: Sigma fields and Probability measures, Probability Axioms, Lebesgue integration and expectation, Measure-theoretic independence, Borel-Cantelli Lemmas, Modes of probabilistic convergence, Weak and strong laws of large numbers, and Central limit theorems.
Stat 262. Nonparametric Inference
Thursday, 6:10pm-8:40pm
Instructor: Dr. S. Kundu
This course will discuss inferential methods when the form of the underlying distribution is not specified or is only partially specified. Topics to be covered in this course include: U-statistics, rank tests, locally most powerful rank tests, one and two-sample tests, asymptotic distribution theory, asymptotic relative efficiency, nonparametric point estimates and confidence intervals, goodness of fit tests.
Stat 263. Advanced Statistical Theory I
Tuesday, 6:10pm-8:40pm
Instructor: Dr. T. Nayak
This is an advanced course on principles and theory of statistical inference. Topics include: sufficiency, ancillarity, completeness, unbiased estimation, Cramer-Rao inequality, Bayesian estimation, admisibility, hypotheses testing.
Stat 287. Modern Theory of Survey Sampling
Monday, 6:10pm-8:40pm
Instructor: Dr. P. Chandhok
The main objectives of the course are to provide a rigorous treatment of sampling theory and its applications. This course will introduce the following topics: simple random sampling with and without replacement, systematic sampling, unequal probability sampling with and without replacement, ratio estimation, difference estimation and regression estimation.
Stat 289. Statistical Method for Genetics
Monday, 6:10pm-8:40pm
Instructor: Dr. Z. Li
There are three objectives of this course: 1) to provide an introduction of quantitative genetics for students without any genetics background; 2) to give a rigorous statistical treatment of some genetic problems; 3) to introduce current research topics in the area of statistical methods for genetic analysis.
Continuing the topic begun in October 2003, the difference between general linear models and models using generalized estimating equations (GEE's) is covered. The available correlation structures in PROC GENMOD are discussed and GENMOD is used to fit a longitudinal data model. Finally, the concepts behind generalized linear mixed models are discussed and a longitudinal data model is fit using the GLIMMIX macro.
SIGSTAT is the Special Interest Group in Statistics for the CPCUG, the Capital PC User Group, and WINFORMS, the Washington Institute for Operations Research Service and Management Science.
All meetings are in Room S3031 (Food Safety and Nutrition Room), 1800 M St, NW from 12:30 to 1:30. Enter the South Tower and take the elevator to the 3rd floor to check in at the guard's desk.
First-time attendees should contact Charlie Hallahan, 202-694-5051, hallahan@ers.usda.gov and leave their name. Directions to the building and many links of statistical interest can be found at the SIGSTAT website, www.cpcug.org/user/sigstat/
Items for publication in the August 2004 WSS NEWS should be submitted no later than July 27, 2004. E-mail items to Michael Feil at michael.feil@usda.gov.
|
|||||||||||||||||||||||
|
First posted June 7, 2004 |
http://www.scs.gmu.edu/%7Ewss/wss0406.shtml |