A wholesale company buys sugar from a sugar mill and then supplies sugar to the

Question

A wholesale company buys sugar from a sugar mill and then supplies sugar to the retail shops. The sugar mill buys their sugar cane from the cane farmers of a region. Cane production is largely dependent on the weather condition such as rain and temperature of the region as well as extreme weather condition such as flood. The manager of the wholesale company is always worried about competitors' reactions and changes in sales. Both the wholesale company and the sugar mill manager need to know the current and future trend of sugar supply, sales and price in order to maximise company's profit. Q. What type of statistical model should the sugar mill use to predict the future sugar production, based on the past trends in sugar sales and sugarcane supply?

Explanation / Answer

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables (or 'predictors'). More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed.

Regression analysis is widely used for prediction and forecasting. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables

Here dependent variable is future sugar production and independent variables are past trends in sugar sales and sugarcane supply.

Hence using regression model sugar mill can predict the future sugar production.

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