18.05 Lecture Notes - Lecture 5: Mit Opencourseware
Document Summary
Fitting a line to data using the mle. Suppose you have bivariate data (x1, y1), . A common model is that there is a linear relationship between x and y, so in principle the data should lie exactly along a line. However since data has random noise and our model is probably not exact this will not be the case. What we can do is look for the line that best ts the data. To do this we will use a simple linear regression model. For bivariate data the simple linear regression model assumes that the xi are not random but that for some values of the parameters a and b the value yi is drawn from the random variable. Yi axi + b + i where i is a normal random variable with mean 0 and variance 2 . We assume all of the random variables i are independent.
