the co-efficient of determination or -squared so how do know how good my regression ishow well does my line fit my datathat' where -squared comes inand -squared is also known as the coefficient of determination againsomeone trying to sound smart might call it thatbut usually it' called -squared it is the fraction of the total variation in that is captured by your models so how well does your line follow that variation that' happeningare we getting an equal amount of variance on either side of your line or notthat' what -squared is measuring computing -squared to actually compute the valuetake minus the sum of the squared errors over the sum of the squared variations from the meansoit' not very difficult to computebut againpython will give you functions that will just compute that for youso you'll never have to actually do that math yourself interpreting -squared for -squaredyou will get value that ranges from to now means your fit is terrible it doesn' capture any of the variance in your data while is perfect fitwhere all of the variance in your data gets captured by this lineand all of the variance you see on either side of your line should be the same in that case so is badand is good that' all you really need to know something in between is something in between low -squared value means it' poor fita high -squared value means it' good fit as you'll see in the coming sectionsthere' more than one way to do regression linear regression is one of them it' very simple techniquebut there are other techniques as welland you can use -squared as quantitative measure of how good given regression is to set of data pointsand then use that to choose the model that best fits your data