The most important goal of statistics is to analyze real data from the world around us.
If this information is analyzed accurately and correctly, the results will help us in many important decisions.
One of the real data around us that is very important to analyze is data related to water consumption. Given that
Iran is located in the semi-arid climatic region of the world, it is necessary to take deep steps to predict and select
the best and most appropriate accurate water consumption models, which are necessary for national macro-decisions. In analyzing real data, the researcher may encounter the problem of collinearity and outliers. Robust methods are used to analyze data sets with outliers and the ridge approach is a method used to analyze data sets with collinearity. The limitation on models also arises from the use of non-sample data in estimating regression coefficients. This article discusses the modeling of water consumption data using a robust stochastic constrained ridge approach.