meaning that each random heightdenoted by heightsatisfies height shoe weight ewhere is normally distributed error term with mean and variance thusthe model has parameters before analyzing the model we present scatterplot of all pairs of variablesusing scatter_matrix height model ols(height ~shoeweight "datasurvey fit model fit (axes pd plotting scatter_matrix survey [['height ','shoe ','weight ']]plt show ( shoe weight height weight shoe figure scatterplot of all pairs of variablesheight (cm)shoe (cm)and weight (kgas for the simple linear regression model in the previous sectionwe can analyze the model using the summary method (below we have omitted some output)fit summary (dep variable model method no observations df residuals df model height ols least squares rsquared adj rsquared fstatistic prob (fstatistic ) - log likelihood - aic bic =====================================================================coef std err >| [ intercept