Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

Using multiple linear regression, we were able to predict 79% of the variation in NO2 levels with four variables: traffic density within 40–300 m of the sampling location, traffic density within ...

The association between each land-use variable and NO2 concentrations at 68 locations in Rome in 1995 and 1996 was assessed by univariate linear regression and a multiple linear regression model ...

However, achieving this understanding can be complicated when using multiple regression, because the relative importance of explanatory variables, as measured by regression coefficients, can shift ...

Regression models using fractional polynomials of the covariates have appeared in the literature in an ad hoc fashion over a long period; we provide a unified description and a degree of formalization ...