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Hauptverfasser: Mukherjee, Himadri, Bhonge, Pratham
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2501.14845
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author Mukherjee, Himadri
Bhonge, Pratham
author_facet Mukherjee, Himadri
Bhonge, Pratham
contents This paper investigates the distribution of marks obtained by students across multiple courses to explore whether the data conforms to a skew-normal distribution. Traditional methods for assessing normality, such as the Shapiro Wilk test, often reject normality in datasets with evident skewness. To address this, we apply a modified Shapiro Wilk test tailored for skew-normal distributions, as described in the literature, to evaluate the suitability of skew-normal models for these datasets. The analysis includes both classical and modified tests, complemented by visualizations such as histograms and Q-Q plots of transformed data. Our findings highlight the relevance of using specialized statistical methods for skew normality, offering valuable insights into the characteristics of academic performance data. This study provides a framework for robust statistical analysis in educational research, emphasizing the need to account for distributional properties when analyzing student performance metrics.
format Preprint
id arxiv_https___arxiv_org_abs_2501_14845
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Assessing Skew Normality in Marks Distribution, a Comparative Analysis of Shapiro Wilk Tests
Mukherjee, Himadri
Bhonge, Pratham
Methodology
Statistics Theory
62E10, 62P99, 97U70
This paper investigates the distribution of marks obtained by students across multiple courses to explore whether the data conforms to a skew-normal distribution. Traditional methods for assessing normality, such as the Shapiro Wilk test, often reject normality in datasets with evident skewness. To address this, we apply a modified Shapiro Wilk test tailored for skew-normal distributions, as described in the literature, to evaluate the suitability of skew-normal models for these datasets. The analysis includes both classical and modified tests, complemented by visualizations such as histograms and Q-Q plots of transformed data. Our findings highlight the relevance of using specialized statistical methods for skew normality, offering valuable insights into the characteristics of academic performance data. This study provides a framework for robust statistical analysis in educational research, emphasizing the need to account for distributional properties when analyzing student performance metrics.
title Assessing Skew Normality in Marks Distribution, a Comparative Analysis of Shapiro Wilk Tests
topic Methodology
Statistics Theory
62E10, 62P99, 97U70
url https://arxiv.org/abs/2501.14845