Simple linear regression
Many problems we find in science, engineering, and business are of the following form. We have a continuous variable, and by continuous we mean a variable represented using real numbers (or floats if you wish). We call this variable the dependent, predicted, or outcome variable. And we want to model how this dependent variable depends on one or more variables, which we call independent, predictor, or input variables. The independent variable can be continuous or it can be categorical. These type of problems can be modeled using linear regression. If we have only one independent variable we may use a simple linear regression model problem; if we have more than one independent variable then we may apply a multiple linear regression model. Some typical situations that linear regression models can be used in are as follows:
Model the relationship between factors like rain, soil salinity, and the presence/absence of fertilizer in crop productivity. Then answer questions...
