Teaching Robust Methods for Exploratory Data Analysis.

Abstract

This paper is an introduction to some of the ideas of robust statistical methods as was presented to the Fourth International Congress for Mathematical Education, session on Exploratory Data Analysis. Most statistical methods taught and used today are very sensitive to bad or atypical data and can give meaningless results in their presence. Robust methods protect against these undesirable effects and can be incorporated into the teaching of statistics at all levels of complexity. We discuss the need for robust methods to supplement (not replace) standard procedures, suggest some considerations regarding teaching, and review some of the fundamental concepts of robust estimation. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1980
Accession Number
ADA092661

Entities

People

  • Andrew F. Siegel

Organizations

  • Princeton University

Tags

DTIC Thesaurus Topics

  • Arithmetic
  • Buildings And Structures
  • Data Analysis
  • Data Mining
  • Data Science
  • Data Sets
  • Education
  • Information Science
  • Military Research
  • New York
  • Normal Distribution
  • Order Statistics
  • Standards
  • Statistics
  • Students
  • Universities

Fields of Study

  • Mathematics

Readers

  • Economics
  • STEM Education
  • Theoretical Analysis.