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Using Card Games for Conditional Probability, Explaining Gamma vs. Poisson Distributions, and Weighing Central Limit Theory

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Conference

2016 ASEE Annual Conference & Exposition

Location

New Orleans, Louisiana

Publication Date

June 26, 2016

Start Date

June 26, 2016

End Date

August 28, 2016

ISBN

978-0-692-68565-5

ISSN

2153-5965

Conference Session

Mathematics Division Technical Session 1

Tagged Division

Mathematics

Page Count

9

DOI

10.18260/p.27135

Permanent URL

https://peer.asee.org/27135

Download Count

1271

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Paper Authors

biography

Roes Arief Budiman P.Eng. University of Calgary

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Received PhD in Materials Science and Engineering at University of Toronto in 2001. Currently a Senior Instructor at University of Calgary and have been teaching Probability & Statistics for Engineers course in the past three years. Maintain a small research group (1 PhD, 1 MEng) on pipeline failure and reliability.

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Abstract

Students taking probability course for the first time are often struggling with conditional probability. To help explain the concept better, card games are used to explain especially differences of conditional probabilities of sequential and simultaneous card draws. Several card game experiments are discussed and typical probability results are shown and compared with predictions. These simple experiments can be demonstrated in classroom and students can use them to test the predictions. Another concept students often struggle is distinguishing gamma from Poisson distribution. An identity connecting them, generalizing the connection between exponential and Poisson distribution, will be used to discuss their differences and to point out nuances in the wording of some probability problems that yield different answers when both distributions are used. Lastly, a teaching tool for explaining central limit theorem is discussed based on guessing weights of books. This guessing game proves useful to explain sampling distribution.

Budiman, R. A. (2016, June), Using Card Games for Conditional Probability, Explaining Gamma vs. Poisson Distributions, and Weighing Central Limit Theory Paper presented at 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana. 10.18260/p.27135

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