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Packing Pickles: Picking and Performing a Statistical Test



Co Authors:

Christopher J. Cheng
Department of Food, Bioprocessing and Nutrition Sciences
North Carolina State University

Clinton Stevenson
Department of Food, Bioprocessing and Nutrition Sciences
North Carolina State University
cdsteve3@ncsu.edu

Abstract:

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.).

Objectives:
  • Perform statistical two-sample t tests.
  • Determine what situations warrant statistical testing.
Keywords: Statistics; quality control; hypothesis testing; t test; statistical test; statistical significance; experimental design; data analysis; null hypothesis; food industry; pickles
Topical Area: N/A
Educational Level: High school, Undergraduate lower division, Undergraduate upper division
Formats: PDF
Type/Method: Analysis (Issues), Interrupted
Language: English
Subject Headings: Statistics   Food Science / Technology  
Date Posted: 12/22/2014
Date Modified: N/A
Copyright: Copyright held by the National Center for Case Study Teaching in Science, University at Buffalo, State University of New York. Please see our usage guidelines, which outline our policy concerning permissible reproduction of this work.

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Answer Key


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Supplemental Materials


The following supplemental materials may be used with this case study:

  Teacher Guide: Math and Statistics hhmi/
This 42-page guide covers the following topics: measures of average (mean, median, and mode), variability (range and standard deviation), uncertainty (standard error and 95% confidence interval), Chi-square analysis, student t-test, Hardy-Weinberg equation, frequency calculations, and more. Produced by HHMI BioInteractive.
  Spreadsheet Tutorial 4: t-Test hhmi/
This tutorial covers the t-test, including how to calculate t-values manually, a table of critical values of t, and how to use the built-in TTEST function to perform a t-test. Also includes doing a t-test using Excel’s Analysis Toolpak. Produced by HHMI BioInteractive.



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