Since 1960s, in which the computer graphics system first appeared, various graphical techniques have been introduced for regression diagnostics and they have been remarkably developed. In particular, animation, one of the dynamic graphical methods which Cook and Weisberg (1989) proposed helps to show the effect of adding variables or observations to a model, or removing them from a model on the regression results. We present the added variable plots (AVP) with animation, which can be used as an optical tool of understanding the affect of some variables or observations on other variables, and the detrended added-variable plots (DAVP) with animation, through which it is possible to find out whether specific variables or observations have an effect on the nonlinearity of other variables or not.