Productivity Prediction of Garment Employees using Multiple Linear Regression
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DOI:
https://doi.org/10.59287/ijanser.644Keywords:
Multiple Linear Regression, Multicollinearity, Variable, Statistical, TransformationAbstract
This paper presents a multiple linear curve fitting method for finding how the change of manipulated variables affect the final result using productivity prediction of garment employees data set. To perform fitting, a function is defined, which depends on the parameters that measures the closeness between the data and model. The simplest form of modelling is linear regression, which is the prediction of one variable from another. When the relationship between a few variables are assumed to be linear, then multiple linear regression will be used to model the relationship between a continuous response variable and continuous or categorical explanatory variables.
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