131st Annual Meeting Joint Statistical Meetings of the American Statistical Association,The Blometrlc Society,Enar and Wnar,The Institute of Mathematical Statistics

(We are attempting to inaugurate a different type of questions and answers page in this issue of the American Statistician. Our purpose is to stimulate an interest in conceptual and measurement problems which arise in the course of statistical work and which require discussion apart from purely mathematical considerations. It is hoped that our readers will find this approach of interest and value. We are inviting questions of this type.)     

2011 Kansas Library Association Annual Meeting

Abstract

The annual meeting of the Kansas Library Association (KLA) was held April 6–8, 2011, in Topeka, KS, giving a brief respite and spring rejuvenation to academic and public librarians in the state.     

American Statistical Association Style Guide

This article contains the American Statistical Association Style Guide published in The American Statistician volume 40 issue 1, in 1986. To see the current version of the style guide please click here.     

Potomac Technical Processing Librarians 77th Annual Meeting

Abstract

Serials Review visits the Immigration History Research Center (IHRC) in Minneapolis, Minnesota. The Center's mission is to teach the importance of immigration studies and promote the use of the IHRC collections, which concentrate on immigration to America from 1880 through the beginning of the twentieth century from eastern, central, and southern Europe and the Near East. The Center also supports Collections Online: A Digital Library of American Immigration &; Ethnic History (COLLAGE), a database of images and narratives from the archives. Serials Review 2003; 29:151–153.     

Lemuel Shattuck,Statist Founder of the American Statistical Association

Polynomial regression of degree p in one independent variable χ is considered. Numerically large sample correlations between χ^α and χ^β, α < β, a, β = 1, ···, p, may cause ill-conditioning in the matrix to be inverted in application of the method of least squares. These sample correlations are investigated. It is confirmed that centering of the independent variable to have zero sample mean removes nonessential ill-conditioning. If the sample values of χ are placed symmetrically about their mean, the sample correlation between χ^α and χ^β is reduced to zero by centering when α + β is odd, but may remain large when α + β is even. Some examples and recommendations are given.