2.3 Residuals

standard error

the standard deviation of the residuals - when assumptions and conditions are met, the spread residuals can be described using this and the 68, 95, 99.7 rule

s_e

the standard error of a regression

R²

shows the fraction of the variability of the response variable that is accounted for by the least squares linear regression model - also commonly named the ‘coefficient of variability’, and is the square of the correlation between x and y variables

residuals

the difference between observed data values and the corresponding values predicted by the mathematical mdoel

s_e = √ (Σ e²) / (n-2)

the formula for the standard error of a regression

e

the variable that represents any individual residual; observed value - predicted value