figure - normal plot ( - ploton the left and histogram to confirm normality on the right any deviation from the straight line in normal plot or skewness/multi-modality in histogram shows that the data does not pass the normality test  -squaredgoodness of fit -squared or the coefficient of determination is another measure used to check for goodness of fit for regression analysis it is measure used to determine if the regression line is able to indicate the variance in dependent variable as explained by the independent variables(sr-squared is numeric value between and with pointing to the fact that the independent variable(sare able to explain the variance in dependent variable values closer to are indicative of poor fitting models cross validation as discussed in model generalization is also an important aspect of working on data science problems model which overfits its training set may perform poorly on unseen data and lead to all sorts of problems and business impacts hencewe employ -fold cross validation on regression models as well to make sure there is no overfitting happening modeling the stage is now set to start modeling our bike sharing dataset and solve the business problem of predicting bike demand for given date time we will utilize the concepts of regression analysis discussed in the previous section to model and evaluate the performance of our models the dataset was analyzed and certain transformations like renaming attributes and type casting were performed earlier in the since the dataset contains multiple categorical variablesit is imperative that we encode the nominal ones before we use them in our modeling process