nominally significantp < 0.05
We checked statistical assumptions of nominally significant ( p < 0.05) linear regression models (Parts 2 and 6) by means of visual inspection of the following residual plots: correct specification of the model (residuals vs. fitted values), normality of residuals (normal Q–Q), homoscedasticity of residuals (scale location) and existence of outliers or influential data points (residuals vs. leverage).