Choosing the right model: Linear regression model vs simulation model. Regression is a statistical method used in finance, investing and other disciplines that attempts to determine the strength and character of the relation between one dependent variable and a series of other variables, independent variables (Beers, 2023). Simulation imitates the operation of real world process or systems with the use of models. The model represents the key behaviors and characteristics of the selected process or systems while the simulation represents how the model evolves under different conditions over time (TWI, 2024). The proper model must be selected while attempting to solve problems that actually exist in the real world in order to produce accurate and insightful answers. The two most popular models used in data analysis are simulation models and linear regression models. While each has advantages and disadvantages, being aware of their main distinctions can aid in selecting the best model for the given issue