Linear inference method in agriculture and livestock an application on (quantile regression analysis)

Linear or non-linear models, which are conducted to determine the relationships between the variable considered as response, outcome or dependent variable, and the traits considered as explanatory (independent) variable or variables, are generally called Regression models. Parameter estimation in Simple or Multiple linear regression models is mostly performed by the Least Squares method. However, some assumptions must be provided for this method. In cases where these assumptions are not met, one of the alternative methods, quantile regression, can be used. The quantile regression model attempts to model the relationship between the set of explanatory or independent variables and the percentile or quantiles of the dependent variable, which were specifically determined by the researcher. In this study, general information about the Quantile regression method was given and the results obtained from the Quantile regression and standard multiple regression analysis were evaluated by applying the combination of 2 different sample sizes and number of variables and 4 different quantile ratios