Keywords

Regression analysis, Rubber, Artificial

Abstract

The goal of this study is to find a more organized and directed approach to build models for mixture systems. An attempt is made to generate and then compare Scheffe (mixture) models with those generated by McGee using the ‘conventional’ method for neoprene data. The models are judged on their ability to predict physical properties of neoprene by comparing the following: predicted and actual values by inspection; the calculated % error of prediction; the squared multiple correlation coefficients; adjusted squared multiple correlation coefficients; the Fisher statistic and significance probability. Scheffe models do not have an intercept term and test statistics which appear on the computer printout are inflated. Pseudocomponents and Scheffe-equivalent models are procedures used to obtain accurate test statistics to describe the selected Scheffe models. The effectiveness of these two procedures is evaluated. Results indicate that Scheffe models are better predictors for the physical properties of neoprene than those generated by McGee using the ‘conventional’ method in 1980. Scheffe-equivalent equations are found to be more reliable than pseudocomponents for generating accurate test statistics to describe the selected Scheffe models.

Graduation Date

1986

Semester

Spring

Advisor

McGee, William W.

Degree

Master of Science (M.S.)

College

College of Arts and Sciences

Department

Chemistry

Degree Program

Industrial Chemistry

Format

PDF

Pages

89 p.

Language

English

Rights

Public Domain

Length of Campus-only Access

None

Access Status

Masters Thesis (Open Access)

Identifier

DP0020310

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