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Bootstrap Pearson test for difference in discrete distributions

conference contribution
posted on 2023-05-23, 14:51 authored by Nataliya NikolovaNataliya Nikolova, Martin Crees-MorrisMartin Crees-Morris, Tsonev, Y, Kiril TenekedjievKiril Tenekedjiev
one-dimensional discrete random variable X describes two populations. A random sample is drawn from each. We formalize a generic statistical test to determine whether the samples provide enough evidence that the distributions of X in the two populations are different. After showing the drawbacks of the existing analytical tests, we develop a Bootstrap procedure with Pearson test statistic calculated from a contingency table. The p-value is estimated using the simulated conditional distribution of the test statistics under null hypothesis for equality of population distributions. Compared to analytical tests, our procedure gives higher precision and decreases uncertainty in both small and big samples. We apply our procedure to survey data on leadership capabilities in academia among two samples of respondents. We take one question from the survey and analyse significance of differences in the responses depending on three criteria.

History

Publication title

Proceedings of the IEEE International Conference on Automatics and Informatics (ICAI)

Pagination

1-6

ISBN

978-1-7281-9308-3

Department/School

Australian Maritime College

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

New Jersey, United States

Event title

IEEE International Conference on Automatics and Informatics (ICAI)

Event Venue

Virtual Conference, Online (Varna, Bulgaria)

Date of Event (Start Date)

2020-10-01

Date of Event (End Date)

2020-10-03

Rights statement

Copyright 2020 IEEE

Repository Status

  • Restricted

Socio-economic Objectives

Information systems; Expanding knowledge in engineering

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