The distance between the model's prediction and an observation. The squared distance between the model's prediction and an observation. QUESTION 3 How do we find the linear model that best fits a dataset? O Pick the model that minimizes the square root of the sum of the squared residuals. Pick the model that minimizes the sum of the residuals. Pick the model that looks like it goes through the data the best. Pick the model that minimizes the sum of the squared residuals. QUESTION 4 Which of these in NOT an assumption of the least square method for fitting a linear model bet The data in the x yariahle has a normal distribution