Multiple regression analysis using climate variables

Abstract

Regression analysis is very useful when it comes to study the relationship between variables. Regression analysis can identify the cause and effect of one variable to another variable. Variables is the main part in regression analysis. There are dependent variable (or criterion variable) and independent variable (or predictor variable). In multiple regression, the independent variables can be added more in the model then explain the cause and effect of dependent variable in more variations. Hence, dependent variable can be predicted by building better models using multiple regression analysis. The objective of this study comprises of (i) to determine correlation between temperature, humidity, wind, solar radiation and evaporation; and (ii) to build relationships between predictand with predictors using multiple linear regression.