Multiple linear regression uses two or more independent variables to predict a dependent variable. The result is an equation you can use to estimate future outcomes based on known data.

With only one variable in the model, it is unclear whether Visa affects the S&P 500 prices, if the S&P 500 affects V prices, or if some unobserved third variable affects both prices.

Simple linear regression relates two variables (X and Y) with a straight line (y = mx + b), ... so you can choose the correct regression model, whether linear or nonlinear.