A new lab activity for first-year introductory physics teaches students to use data to drive decision-making in science and engineering processes. Using the popular PDCA (plan-do-check-act) cycle, students manufacture a small sample of ball bearings out of modeling clay. By statistically analyzing their sample, they determine whether a larger shipment will meet tolerance levels specified by the lab TA. They then make decisions on ways to change their manufacturing process to improve results, employing another round of data analysis to confirm whether the change improved their process. Judging by student comments, such an activity reinforces the conceptual basis for numerous statistical properties, helps distinguish many commonly confused statistical concepts, and reinforces the use of data in process management. This activity can be incorporated into either algebra-based or calculus-based physics labs and, because it does not rely on background knowledge of physics concepts, should prove ideal for the early weeks of lab instruction.
References
American Recovery and Reinvestment Act of 2009: Law, explanation and analysis: P.L. 111-5, as signed by the President on February 17, 2009.
The target value is called the nominal value in Six Sigma parlance.
Teams should avoid processes that center on a particular team member conducting specific tasks. Not only does this make the manufacturing process take longer, it is also undesirable to have any process depend on who is carrying out the task.
These changes were prompted by the fact that the standard error predicts confidence intervals for the population only when the population is substantially larger than the sample.
