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Activity Number: 262
Type: Contributed
Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract #314812
Title: The Minimization Process in the Correlation Estimation System Compared to Least Squares in Linear Regression
Author(s): Rudy Gideon*
Companies:
Keywords: regression ; estimation by correlation coefficients ; minimization over order statistics ; ACT scores ; SAT scores
Abstract:

This presentation contains a new system of estimation starting with correlation coefficients that rivals least squares and for much data does better. One example of SAT and ACT data is used to illustrate minimization through the Correlation Estimation System (CES) in a two-variable linear regression; in this example the CES results appear to be a better representation of the meaning of the data. This result is completely typical; it was not cherry-picked. If you are a least squares-bible toting statistician then what you hear in this talk is blasphemy, but if you are a more secular statistician then you may appreciate a rival estimation system that should be widely used.

Authors who are presenting talks have a * after their name.

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