solinear regression is fitting straight line to set of observations for examplelet' say that have bunch of people that measured and the two features that measured of these people are their weight and their heighti' showing the weight on the -axis and the height on the -axisand can plot all these data pointsas in the people' weight versus their heightand can say"hmmthat looks like linear relationshipdoesn' itmaybe can fit straight line to it and use that to predict new values"and that' what linear regression does in this examplei end up with slope of and -intercept of which define straight line (the equation of straight line is =mx+bwhere is the slope and is the -interceptgiven slope and yinterceptthat fits the data that have besti can use that line to predict new values you can see that the weights that observed only went up to people that weighed kilograms what if had someone who weighed kilogramswelli could use that line to then figure out where would the height be for someone with kilograms based on this previous data don' know why they call it regression regression kind of implies that you're doing something backwards guess you can think of it in terms of you're creating line to predict new values based on observations you made in the pastbackwards in timebut it seems like little bit of stretch it' just confusing term quite honestlyand one way that we kind of obscure what we do with very simple concepts using very fancy terminology all it isis fitting straight line to set of data points