00:01
So we have a statistics student who is trying to determine if the airfare, what we'll call y, is explained by the distance x of a flight.
00:20
So does x have some prediction ability on y? is there some linear relation between these distances, the distance and airfare? and so this person ended up making a model, y hat equals beta not plus beta 1x.
00:43
And for our question here, these coefficients don't really matter the slope coefficient and the intercept coefficient.
00:49
Those don't really matter because the question is about this number, r squared, which we're given is 63 .2%.
00:57
And this term, this r squared, called the coefficient up to term, is the in general terms, it's the following.
01:10
It's the percent variation in y that can be explained by the variation we see in x.
01:17
And since this is a linear model, we're talking about y's linear relationship with x.
01:23
So in our case here, where we're talking about y is price, x is distance, we'd say this is 63 % of the variation...