Title

A Monte Carlo Comparison of Robust and Resistant Estimators of Bivariate Correlation

Author

Bernadette Bonnie Baranowski, Syracuse University

Date of Award

1980

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Psychology

Advisor(s)

Silas Halperin

Keywords

Gaussian, Error distribution, Normal myth

Subject Categories

Statistics and Probability

Abstract

Introduction:

Whenever we mention the word statistics or statistical procedures, the mean, standard deviation, Pearson correlation coefficient and normal curve are the concepts that come to mind. The Gaussian probability distribution (affectionately known as normal) and its companion least-squares estimators are the foundations for classical statistical procedures and measurement theory. ... Unfortunately the limitations and assumptions are often ignored without regard to what the resulting statistics may or may not represent if our data are not truly Gaussian.

Access

Restricted

Recommended Citation

Baranowski, Bernadette Bonnie, "A Monte Carlo Comparison of Robust and Resistant Estimators of Bivariate Correlation" (1980). Psychology - Dissertations. 138.
https://surface.syr.edu/psy_etd/138

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