In practice, linear regression involves collecting data on chemical concentrations and biological responses, followed by plotting this data on a scatter plot. A regression line is then fitted through the data points to describe the relationship. The slope of the line indicates the rate of change of the response variable with respect to changes in the predictor variable, while the intercept provides the expected response when the predictor is zero. This model can then be used to make predictions and infer causality.
