Collection of angular velocity and acceleration sensor data is prone to seemingly random “noisy” variations, even when the associated motion appears to be smooth to the observer. The easiest way to compensate for this variation is to compute the mean value for the duration of such a random variation. The up-and-coming, but not yet leased, ** CloudLab** software from PocketLab provides an easy way to compute means, standard deviations, and other statistics for a selected region of PocketLab data.

This lesson provides a sneak preview of this CloudLab feature, allowing students to compute the radius of a curve on an Anki OVERDRIVE supercar racetrack from data collected by PocketLab’s angular velocity and acceleration sensors. This lesson is motivated from a previous lesson by the author, in which the radius of curvature of a gradual street turn is determined with PocketLab mounted in an automobile. The new lesson brings the previous lesson *into the classroom* by using a toy race car set rather than an actual automobile—opening an instructive investigation up to a much larger audience of students.