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Grassy Narrows and Muskrat Falls Dam: The Central Limit Theorem and a t-test

Author(s): Paul Miller

Everett Community College

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Summary:
Students are introduced to concepts of sampling distributions and hypothesis testing using a simulation applet, elementary hypothesis tests, t-tests, and p-values as they compare a given fish population for methylmercury levels (using real and…

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Students are introduced to concepts of sampling distributions and hypothesis testing using a simulation applet, elementary hypothesis tests, t-tests, and p-values as they compare a given fish population for methylmercury levels (using real and hypothetical data) against real-world mercury standards.

Description

The module is divided into parts and can be done in-class, online, or as homework.  There are areas where additional resources are provided for students/courses that need instructional material not provided in the case study.  In addition, there are opportunities to expand particular sections for classes that would like to emphasize certain content areas.  Overall, students are introduced to concepts of hypothesis testing using elementary hypothesis tests, t-tests, p-value (and more) as they compare a given fish population for methylmercury levels (using real and hypothetical data) against real-world mercury standards in fish (in Canada).  Additionally, students will be encouraged to research for themselves as well as have an open philosophical discussion at the close of the module.

In this version, two smaller assignments have been added that simulate the process of creating a sampling distribution of the sample mean and compare the empirical distribution to the sampling distribution as described by the Central Limit Theorem. In the second assignment, students are asked to perform the same one sample t-test that was presented in the original version.

This material is based upon work supported by the National Science Foundation under Grant No. 1919613. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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