Advances and Applications in Statistics

The Advances and Applications in Statistics is an internationally recognized journal indexed in the Emerging Sources Citation Index (ESCI). It provides a platform for original research papers and survey articles in all areas of statistics, both computational and experimental in nature.

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BIMODAL DISTRIBUTIONS FOR THE UNDERGRADUATE STATISTICS CURRICULUM

Authors

  • Mohamed Y. Hassan
  • Ibrahim Abdalla
  • Ali Gargoum

Keywords:

bigdata, Apache Spark, kernel density estimates, bimodal distributions, excess mass test, statistics curriculum

DOI:

https://doi.org/10.17654/0972361723003

Abstract

Bimodal data arises from various sources in different disciplines, including but not limited to financial, medical, environmental, technological, social, and educational fields. However, one of the biggest challenges undergraduate students across various disciplines face in modeling and analyzing these data is the lack of flexible bimodal distributions that could capture patterns. Although statistics programs are aware of the importance of bimodal data, most undergraduate textbooks lack bimodal distributions in their contents. Including these distributions in the curriculum would provide students with the tools needed to analyze bimodal data and enrich mathematical statistics courses. This paper introduces existing univariate bimodal probability distributions for modeling these types of data efficiently in an undergraduate curriculum. Those distributions are flexible and in closed form. Some examples, using real-world data, are presented to demonstrate the importance of these distributions.

Received: June 26, 2022; Accepted: August 1, 2022; Published: December 19, 2022

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Published

24-09-2025

Issue

Vol. 84 (2023)

Section

Articles

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How to Cite

BIMODAL DISTRIBUTIONS FOR THE UNDERGRADUATE STATISTICS CURRICULUM. (2025). Advances and Applications in Statistics , 84, 33-50. https://doi.org/10.17654/0972361723003

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