Statistics of Obese Patients - Essay Example

The above scatter diagram shows that there can be a relationship between the change in triglyceride level and the change in weight because the data reveals that there is only a single outlier (1.5, 349).

The straight-line regression model should be used with utmost caution when predicting future values. The linear regression model assumes that the data points are scattered around a straight line but unfortunately, there are certain cases in which data points may be scattered around a curve and they can be fitted by the straight line model. This can be a ghastly mistake and it can have profound consequences. For the above scenario, if we predict the change in the triglyceride level of a patient with a loss of 10 kg in weight then this can be a case of extrapolation. By extrapolation, it means that one can not use the regression equation to make predictions for x-values that are outside the range of the x-values in the sample data. Since the x-values in the sample data are limited to (-9.6 kg) therefore it is not viable to predict (-10 kg).