TO STUDY THE EFFECT OF MONOSODIUM GLUTAMATE ON THE URINARY BLADDER

Objective: This study evaluates the appropriateness of statistical tests (Z-test, t-test, and Mann–Whitney U test) for small-sample analyses, addressing common misconceptions and providing evidence-based guidelines for test selection in low-data scenarios. Methods: A comparative framework was developed to assess the performance of parametric and non-parametric tests under varying sample sizes (n<10 to n=30) and distributional assumptions (normal vs. skewed). Normality was tested through Shapiro–Wilk tests, and simulated datasets with controlled variance and outliers were analyzed. Results: Z-tests produced inflated type I errors for n<30 due to reliance on known population variance, a rarely feasible assumption in small samples. T-tests maintained robustness for n≥15 with normal distributions, whereas Mann–Whitney U tests outperformed parametric alternatives for n<15 or non-normal data (skewness >2). Conclusion: Researchers should default to t-tests for small samples with approximate normality and use Mann–Whitney U tests for highly skewed data or n<15. Transparent reporting of sample sizes, normality checks, and test rationale is critical to ensure methodological validity.

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Publication Details

Journal
Asian Journal of Pharmaceutical and Clinical Research
Published
2025-05-07
DOI
https://doi.org/10.22159/ajpcr.2025v18i5.54229
Primary Topic
Biochemical Analysis and Sensing Techniques
Type
article
Field-Weighted Citation Impact
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article

TO STUDY THE EFFECT OF MONOSODIUM GLUTAMATE ON THE URINARY BLADDER

Vijay Gujar, Sanket Dadarao Hiware, Mohan Pethe, Karuna Kachhawa et al.
Asian Journal of Pharmaceutical and Clinical Research
Biochemical Analysis and Sensing Techniques
article

TO STUDY THE EFFECT OF MONOSODIUM GLUTAMATE ON THE URINARY BLADDER

Vijay Gujar, Sanket Dadarao Hiware, Mohan Pethe, Karuna Kachhawa, Aaditya Tarnekar, SAMEER YELWATKAR
article en

Abstract

Objective: This study evaluates the appropriateness of statistical tests (Z-test, t-test, and Mann–Whitney U test) for small-sample analyses, addressing common misconceptions and providing evidence-based guidelines for test selection in low-data scenarios. Methods: A comparative framework was developed to assess the performance of parametric and non-parametric tests under varying sample sizes (n<10 to n=30) and distributional assumptions (normal vs. skewed). Normality was tested through Shapiro–Wilk tests, and simulated datasets with controlled variance and outliers were analyzed. Results: Z-tests produced inflated type I errors for n<30 due to reliance on known population variance, a rarely feasible assumption in small samples. T-tests maintained robustness for n≥15 with normal distributions, whereas Mann–Whitney U tests outperformed parametric alternatives for n<15 or non-normal data (skewness >2). Conclusion: Researchers should default to t-tests for small samples with approximate normality and use Mann–Whitney U tests for highly skewed data or n<15. Transparent reporting of sample sizes, normality checks, and test rationale is critical to ensure methodological validity.

Asian Journal of Pharmaceutical and Clinical Research
Dr. Panjabrao Deshmukh Memorial Medical College (IN), Mahatma Gandhi Institute of Medical Sciences (IN)
Openalex Percentile: Top 88%
Biochemical Analysis and Sensing Techniques
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