It is common in linear regression to [[standardize]] predictor variables and response variables. $x_i = \frac{x_i - \bar x}{\sigma}$ When only the predictor variable(s) is standardized, the coefficient can be interpreted as the effect of a one standard deviation increase in the predictor on the response variable. When both the predictor and response variable are standardized, the intercept is typically zero because the means of both predictor and response variable are aligned at zero. The slope coefficient(s) can be interpreted as the effect in terms of standard deviation on the response of a one standard deviation increase in the predictor(s).