Article Info

Published 13 Aug 2025

Volume / Issue 1 / Issue 4

Pages 55–60

DOI

10.64823/ijter.2504006

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Open Access Research Article

6 pages PDF

COMPARATIVE STATISTICAL INFERENCE OF PM2.5 LEVELS ACROSS INDIAN CITIES : A BOOTSTRAP vs CLASSICAL APPROACH

by , ,

International Journal of Technology and Emerging Research 2025 , 1 (4) , 55–60

10.64823/ijter.2504006

Received: 10 Aug 2025 Published: 13 Aug 2025

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APA

Dr Y Raghunatha Reddy, B. Sravanthi , & S.Rehana (2025). COMPARATIVE STATISTICAL INFERENCE OF PM2.5 LEVELS ACROSS INDIAN CITIES : A BOOTSTRAP vs CLASSICAL APPROACH. International Journal of Technology and Emerging Research, 1(4): 55–60. https://doi.org/10.64823/ijter.2504006

MLA

Dr Y Raghunatha Reddy, et al. "COMPARATIVE STATISTICAL INFERENCE OF PM2.5 LEVELS ACROSS INDIAN CITIES : A BOOTSTRAP vs CLASSICAL APPROACH." International Journal of Technology and Emerging Research, vol. 1, no. 4, 2025, pp. 55–60. https://doi.org/10.64823/ijter.2504006

Chicago

Dr Y Raghunatha Reddy, B. Sravanthi , S.Rehana. "COMPARATIVE STATISTICAL INFERENCE OF PM2.5 LEVELS ACROSS INDIAN CITIES : A BOOTSTRAP vs CLASSICAL APPROACH." International Journal of Technology and Emerging Research 1, no. 4 (2025): 55–60. https://doi.org/10.64823/ijter.2504006

BibTeX

@article{Dr Y Raghunatha Reddy2025comparative, author = {Dr Y Raghunatha Reddy and B. Sravanthi and S.Rehana}, title = {COMPARATIVE STATISTICAL INFERENCE OF PM2.5 LEVELS ACROSS INDIAN CITIES : A BOOTSTRAP vs CLASSICAL APPROACH}, journal = {International Journal of Technology and Emerging Research}, year = {2025}, volume = {1}, number = {4}, pages = {55–60}, doi = {10.64823/ijter.2504006}, }

Abstract

Air pollution remains a pressing environmental and public health challenge in India, with fne particulate matter (PM2.5) posing severe respiratory and cardiovascular risks. This study conducts a comparative statistical inference analysis of daily PM2.5 concentrations for Delhi and Mumbai, based on 2024 data sourced from the Central Pollution Control Board (CPCB). Two estimation approaches are applied: the classical parametric t-based confidence interval method, which assumes normality, and the non-parametric bootstrap approach, which relies on re-sampling without distributional assumptions. The analysis reveals that while Delhi consistently exhibits substantially higher PM2.5 levels than Mumbai, the estimated means and confidence intervals from both methods are closely aligned, indicating that the parametric method’s assumptions are reasonably met in this dataset. The findings underscore the utility of bootstrap methods in validating classical inference, particularly in environmental data analysis, and provide robust evidence for policy-oriented air quality interventions.

Keywords: BOOTSTRAP APPROACH, CLASSICAL APPROACH, confidence intervals, Exploratory Data Analysis

© 2025 The Author(s). Published by IORO Publications. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original author and source are credited, a link to the license is provided, and any changes are indicated.