Application of linear regression and correlation analysis to the poultry processing industry

Abstract

Scope and Method of Study: Within the last decade, poultry processing plants have become much larger. Consequently, investment in such plants is increasing. However, most plant managers still do not possess an adequate, analytical knowledge of the cost function. Linear regression and correlation analysis is one method that may allow individuals to better understand the poultry processing cost function.

Findings and Conclusions: The proper use and application of linear regression and correlation analysis allows individuals to determine the exact influence which variables have on the cost function.

Volume has traditionally been thought to be the main determinant of cost. In this study, volume was indeed the primary factor influencing cost. Management, rather surprisingly, indicated very little correlation as related to cost. However, the variables of sanitation and indirect labor gave high correlations. Before this study was conducted, sanitation and indirect labor were thought to have an insignificant influence on costs.

A more detailed, analytical explanation of the poultry processing cost function is needed. With the aid of linear regression and correlation analysis, such explanation is now possible.