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Clinton Stevenson
Assistant Professor
Department of Food, Bioprocessing and Nutrition Sciences
North Carolina State University
Packing Pickles: Picking and Performing a Statistical Test 

Based on a true story, this case study was created to teach students how to perform statistical tests and determine whether a significant difference exists between two sets of data. Students are faced with the task of assisting Jeff, the manager of a pickle processing plant, who must figure out why there is a larger-than-expected discrepancy between raw materials and final product. Students are given average sample jar weights from the production line and must come up with a suitable hypothesis and appropriate statistical test. While specifically developed for use in a college-level course on quality control in food science, the case has broader applicability for any course that teaches statistical hypothesis testing (e.g., introductory statistics, research experimental design, scientific inquiry, etc.).

Through the Grater: Creating Acceptance Sampling Plans

In this interrupted case study, students assume the role of a quality assurance intern at a plant that manufactures shredded cheese. As there is no formal sampling plan in place to ensure product quality, students are tasked with developing a feasible plan based on specified safety and practicality factors. In the process, they gain experience in adjusting sampling plan parameters to create operational characteristics (OC) curves with particular shapes, as well as practice calculations for acceptance quality limit and limiting quality. The case was developed for an upper-level undergraduate statistical food quality management course. It would also be appropriate for use in any undergraduate or graduate course that covers principles of statistical quality management and quality management tools, such as operations management courses and statistics courses that cover quality management. It is highly recommended that the case be used only with students who are familiar with the concepts taught in undergraduate statistics.