We investigated multivariable function learning--the acquisition of quantitative mappings between multiple continuous stimulus dimensions and a single continuous response dimension. Our subjects learned to predict amounts of time that a ball takes to roll down inclined planes varying in length and angle of inclination. Performance with respect to the length of the plane was quite good, even very early in learning. On the other hand, performance with respect to the angle of the plane was systematically biased early in learning, but eventually became quite good. An extension of K o h and Meyer's (1991) adaptive regression model accounts well for the results. Implications for the study of intuitive physics mcffe generally are discussed.