NIGERIAN JOURNAL OF SCIENCE AND ENVIRONMENT
Journal of the Faculties of Science and Agriculture, Delta State University, Abraka, Nigeria
ISSN: 1119-9008
DOI: 10.5987/UJ-NJSE
Email: njse@universityjournals.org
COMPUTATIONAL IMPLICATIONS FOR THE LEAST SQUARES’ PARAMETERS OF THE SIMPLE LINEAR REGRESSION MODEL UNDER DATA TRANSFORMATION.
DOI: 10.5987/UJ-NJSE.16.037.1 | Article Number: 0D2BA23 | Vol.11 (1) - September 2012
Author: Igabari J.N
Keywords: Scaling Factor, Expected Values, Precision, Least Squares, Regression.
The Least squares method of parameter estimation is considered important due to its relative simplicity, optimal properties and wide economic applications. This paper examines the computational implications for the estimates of regression parameters for a simple linear regression model when there are changes in units of measurement, leading to a new set of data which is a scaled form of the original data. Expressions for the Least Squares estimates of the regression parameters are derived as well as their precision for the new data in terms of the original data.
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