4.2 The Regression Equation
Because we could draw many different lines through the cluster of data points, we need a method to choose the “best” line. The method, called the least-squares criterion, is based on an analysis of the errors made in using a line to fifit the data points.
There is a limited number of possible models (methods may be used to obtain the model after), most likely removed from 2 months: and using Least squares error :
For example ( A ) of e
Finally get:
Calculating 
, finalize model B , it is only the evaluation of the model, the model can be generated using the following methods:
Suppose that a scatterplot indicates a linear relationship between two variables. Then,within the range of the observed values of the predictor variable, we can reasonably use the regression equation to make predictions for the response variable. However,to do so outside that range, which is called extrapolation,
比如减价趋势下的产品价格，离开观测值范围后，价格可能会处于负值状态，所以线性关系必须注明自变量range
In the context of regression, an outlier is a data point that lies far from the regression line
Outliers and Influential Observations
Outliers是偏离直线太远的值
influential observation ： a data point whose removal causes the regression equation (and line) to change considerably
Eg.在加入（2，169）前后的直线发生了巨大变化，所以（2,169）是一个influential observation
解决办法：
1.缩小x的range
2.添加influential observation 周围的点
Nonetheless, we may need either to remove it—thus limiting the analysis to Orions between 4 and 7 years old—or to obtain additional data on 2- and 3-year-old Orions so that the regression analysis is not so dependent on one data point
outlier和influential observation实际上很难分清：An outlier may or may not be an inflfluential observation, and an inflfluential observation may or may not be an outlier. Many statistical software packages identify potential outliers and inflfluential observations.
否则会出现：
该分布实际上应该为curvilinear regression