In catalysis research, understanding the role of different variables such as temperature, pressure, and catalyst composition is crucial. Multicollinearity can obscure the influence of these individual factors, making it challenging to optimize catalytic reactions. It can also lead to inflated standard errors, thereby decreasing the statistical power of the model.
