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Abstract Details
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Activity Number:
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32
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #303351 |
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Title:
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T-Test for Proportions? Making Do When Your Software Can't Do Confidence Intervals for Proportions
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Author(s):
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Matthew Malloure*+ and David Schlueter and Gerald Shoultz and Sango Otieno
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Companies:
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Grand Valley State University and Grand Valley State University and Grand Valley State University and Grand Valley State University
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Address:
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Dept of Statistics, Allendale, MI, 49401,
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Keywords:
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z-intervals ;
t-intervals ;
proportions ;
binary data
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Abstract:
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In Introductory Statistics courses, students are taught how to calculate confidence intervals for the population proportion and the difference between two population proportions. However, statistical software packages often lack syntax for computing such intervals. We show that if categorical data with two levels is recoded in a binary fashion, the resulting t-confidence intervals for one and two sample problems are equivalent to the corresponding z-intervals. We determine mathematically and through simulation at what sample size the t and z intervals can be considered equivalent for various confidence levels.
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