UCD MAT 280 - Statistics- Challenges and Opportunities for the Twenty-First Century

Unformatted text preview:

This is page iPrinter: Opaque thisStatistics: Challenges and Opportunities forthe Twenty-First CenturyEdited by: Jon Kettenring, Bruce Lindsay, & David SiegmundDraft: 6 April 2003iiThis is page iiiPrinter: Opaque thisContents1 Introduction 11.1 The workshop . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 What is statistics? . . . . . . . . . . . . . . . . . . . . . . . 21.3 The statistical community . . . . . . . . . . . . . . . . . . . 31.4 Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Historical Overview 73 Current Status 93.1 General overview . . . . . . . . . . . . . . . . . . . . . . . . 93.1.1 The quality of the profession . . . . . . . . . . . . . 93.1.2 The size of the profession . . . . . . . . . . . . . . . 103.1.3 The Odom Report: Issues in mathematics and statistics 114 The Core of Statistics 154.1 Understanding core interactivity . . . . . . . . . . . . . . . 154.2 A detailed example of interplay . . . . . . . . . . . . . . . . 184.3 A set of research challenges . . . . . . . . . . . . . . . . . . 204.3.1 Scales of data . . . . . . . . . . . . . . . . . . . . . . 204.3.2 Data reduction and compression. . . . . . . . . . . . 214.3.3 Machine learning and neural networks . . . . . . . . 214.3.4 Multivariate analysis for large p, small n. . . . . . . 214.3.5 Bayes and biased estimation . . . . . . . . . . . . . . 224.3.6 Middle ground between proof and computational ex-periment. . . . . . . . . . . . . . . . . . . . . . . . . 224.4 Opportunities and needs for the core . . . . . . . . . . . . . 234.4.1 Adapting to data analysis outside the core . . . . . . 234.4.2 Fragmentation of core research . . . . . . . . . . . . 234.4.3 Growth in the professional needs. . . . . . . . . . . . 244.4.4 Research funding . . . . . . . . . . . . . . . . . . . . 244.4.5 A Possible Program . . . . . . . . . . . . . . . . . . 245 Statistics in Science and Industry 275.1 Biological Sciences . . . . . . . . . . . . . . . . . . . . . . . 275.2 Engineering and Industry . . . . . . . . . . . . . . . . . . . 335.3 Geophysical and Environmental Sciences . . . . . . . . . . . 375.4 Information Technology . . . . . . . . . . . . . . . . . . . . 445.5 Physical Sciences . . . . . . . . . . . . . . . . . . . . . . . . 47iv5.6 Social and Economic Science . . . . . . . . . . . . . . . . . 496 Statistical Education 536.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . 536.2 K-12 and statistics . . . . . . . . . . . . . . . . . . . . . . . 546.3 Undergraduate Statistics Training . . . . . . . . . . . . . . 546.4 Graduate Statistics Training . . . . . . . . . . . . . . . . . . 556.5 Post-Graduate Statistics Training . . . . . . . . . . . . . . . 576.6 Special Initiatives (VIGRE) . . . . . . . . . . . . . . . . . . 586.7 Continuing Education . . . . . . . . . . . . . . . . . . . . . 596.8 Educational Research . . . . . . . . . . . . . . . . . . . . . 597 Summarizing Key Issues 617.1 Developing Professional Recognition . . . . . . . . . . . . . 617.2 Building and maintaining the core activities . . . . . . . . . 627.3 Enhancing collaborative activities . . . . . . . . . . . . . . . 637.4 Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . 648 Recommendations 67A The Workshop Program 69This is page vPrinter: Opaque thisAn executive summaryOn May 6-8, 2002 approximately …fty statisticians from around the worldgathered at the National Science Foundation to identify the future chal-lenges and opportunities for the statistics profession. The workshop waslargely focused on scienti…c research, but all participants were asked to dis-cuss the role of education and training in attaining our long term goals asa profession. The scienti…c committee was placed in charge of producing aworkshop report.A substantial proportion of the report was devoted to describing theunique role of statistics as a tool in gaining knowledge, with the goal ofmaking the report more accessible to the wider audience of its key stake-holders, including universities and funding agencies. This was done largelybecause the role of statistical science is often poorly understood by therest of the scienti…c community. Much of the intellectual excitement of thecore of the subject comes from the development and use of sophisticatedmathematical and computational tools, and so falls beyond the ken of allbut a few scientists.For this reason there is a potential confusion about how statistics relatesto mathematics, and so a portion of the report dealt with separating theidentity of the two. Statistics is no longer, if it ever was, just another mathe-matical area like topology, but rather it is a large scale user of mathematicaland computational tools with a focused scienti…c agenda.The report goes on to identify key opportunities and needs facing thestatistics profession over the next few years. In many ways, the main issuesarise from the tremendous success of statistics in modern …


View Full Document

UCD MAT 280 - Statistics- Challenges and Opportunities for the Twenty-First Century

Download Statistics- Challenges and Opportunities for the Twenty-First Century
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view Statistics- Challenges and Opportunities for the Twenty-First Century and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Statistics- Challenges and Opportunities for the Twenty-First Century 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?