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Abstract Details
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Activity Number:
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354
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #305897 |
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Title:
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An Analysis of Beer Styles
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Author(s):
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Ivan Ramler*+
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Companies:
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St. Lawrence University
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Address:
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Department of Math, CS, and Stats, Canton, NY, 13617, United States
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Keywords:
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cluster analysis ;
interval data ;
beer ;
simulation
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Abstract:
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With the recent surge in the popularity of craft beers and home brewing, the styles of beer that are available to consumers have increased tremendously. However, many beer drinkers are unaware that there are many numerical measurements that are used to describe beer. This paper introduces the numerical measurements used to describe the main styles of beer defined by the Beer Judge Certification Program such as specific gravity, alcohol content, bitterness, and color. An interesting aspect of these characteristics is that they are presented as interval data, for which many common statistical methods don't readily apply. As a result, a novel method for clustering interval data is used to group and describe the similarities in the beer styles.
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