A POST COVID-19 ACADEMIC ENHANCEMENT OF STUDENT UNDERSTANDING OF TYPE II ERROR EXAMPLE IN CLASSICAL HYPOTHESIS TESTING USING A FALSE NEGATIVE RESULT IN A DIAGNOSTIC COVID-19 TEST
Presentation
Overview
Overview
Description
The transmission of a novel coronavirus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes COVID-19 among college students has been an ongoing challenge for universities throughout the world. Student understanding of COVID-19 test results is critical to curtailing the spread of the virus and protecting oneself and others from infection. Specifically, student understanding of the risks of type II error (false negative) and the consequence of ignoring this risk has the potential to prolong the pandemic on university campuses. The focus of this research is on development of a teaching methodology in an “Introduction to Statistics” course to help students better understand the risks and consequences of a type II error in a diagnostic test for COVID-19. An example scenario will be created and utilized to demonstrate how a type II error (false negative) can occur and the risks and implications of this error. The practical nature of the example helps students identify with and understand type II error and how it relates to statistical testing and decision making.
