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Computing confidence intervals for common IR measures

Published

Author(s)

Ian M. Soboroff

Abstract

Confidence intervals quantify the uncertainty in an average and o↵er a robust alternative to hypothesis testing. We measure the performance of standard and bootstrapped con- fidence intervals on a number of common IR measures using several TREC and NTCIR collections. The performance of an interval is its empirical coverage of the estimated statistic. We find that both standard and bootstrapped intervals give excellent coverage for all measures except in situations of abysmal retrieval performance. We recommend using stan- dard confidence intervals when statistical software is handy, and bootstrap percentile intervals as equivalent when no sta- tistical libraries are available.
Proceedings Title
Proceedings of the Workshop on Evaluation for Information Access (EVIA 2014)
Conference Dates
December 8, 2014
Conference Location
Tokyo

Keywords

information retrieval, statistics

Citation

Soboroff, I. (2014), Computing confidence intervals for common IR measures, Proceedings of the Workshop on Evaluation for Information Access (EVIA 2014), Tokyo, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=917303 (Accessed June 14, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created December 9, 2014, Updated February 19, 2017