Wednesday, 10 February 2016
Wednesday, 3 February 2016
REGRESSION ANALYSIS
In scientific research/industrial problem solving often a situation is
encountered where in a number of variables are involved with
possible interactions or relationship among themselves.
Regression
analysis is a statistical technique for investigating and modeling relationship
among these variables in such situations. As an example, consider the Current and Plating Thickness in electroplating.
One may be interested to find out whether they are related and if so, what is
the form of relationship. The relationship may be expressed in the form of an
equation or model connecting one of the variables, known as the response or the
dependant variable (denoted as Y) with one or more other variables known as
explanatory or predictor or independent variables (denoted as X or X1, X2,X3
etc.).
The variables can be either quantitative or qualitative. Examples of quantitative variables are measurable
variables like hardness, tensile strength, diameter, width, etc. Examples of qualitative variables are
good/bad, defective/non-defective, religion, sex, region etc
Applications of regression analysis are numerous and occurs almost every
field, including engineering, quality control, physical and life sciences,
economics, management, social sciences etc.
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