In this segment, we're going to talk about the first check which you have to do for figuring out whether a particular model . . . regression model is adequate.  So the first thing which you should be doing is plotting the data and the model.  So the example which we have taken here is of these particular six data points right here.  So we have these six data points, and what we have done is that we have, these are the six data points which you are seeing right here, and then by using the regression formulas, we are able to get alpha T, alpha as a function of temperature, to be that straight line, this is the y-intercept and this is the slope, and when we are drawing this line, so this is the line which has been just found, which is 0.26393, plus 4.7361 T. So that's the line which we have drawn there, and what we are finding out is that . . . that it is, visually you can see that there's not much wrong with . . . I shouldn't say much wrong with it, but it looks pretty adequate so far as the data is concerned.  So if you just look at this, you can see that it's pretty adequate to show that these six data points which have been chosen and the straight line which has been drawn through it.  So visually, this might seem to be appealing, and you might say that, hey, this looks good enough, but later on we're going to see that this may not be good enough.  So just by plotting the data and plotting the regression model is not an adequate check to see that whether the regression model is adequate.  And that's the end of this segment.