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Journal of Statistics and Management Systems

(Since 1998)
Open Access ·Peer-reviewed·ISSN (Online): 2169-0014·ISSN (Print): 0972-0510

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Monthly Journal: Publishes peer-reviewed aticles on theoretical and applied statistics and management systems, expoloring industrial statistics, actuarial and decision sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Journal of Statistics and Management Systems
Open Access Research Article

Investigating trends in traffic count data utilizing exploratory data analysis and regression analysis

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* Corresponding author · click or hover a name for details

pp. 535–568Vol. 27Issue 3March 2024DOI: 10.47974/JSMS-964XML
Received:
06 Oct 2021
Accepted:
17 May 2022
Published Online:
30 Mar 2024
Article type:
Research Article
Language:
EN
Article no.:
JSMS-964
Pages:
535–568

Abstract

To decipher and understand data collected for any model or decision-making, a statistical investigation into a dataset is necessary to generate every unearthed information in the data through visual means or a summary of the dataset’s patterns. Statistical analysis is utilized to test: normality, randomness, outliers, the relationship between the dependent and the independent variables, and possible temporal and spatial spread in the dataset. In this study, the annual average daily traffic (AADT) dataset obtained from Montana, Minnesota, and Washington were subjected to statistical investigations using descriptive statistics, regression analysis, and hypothesis testing to understand the data patterns. The results generated from exploring the various techniques indicated that the data acquired were generally random. However, the data’s orderliness is not random. The data values had nearly no relationship with the collection locations, thus requiring a model that can generate a precise fit for better decision-making. Data skewness varied from slight to high. Therefore, data ranged from approximating normality and nonnormality with high outliers.

Keywords

Annual average daily trafficExploratory data analysisRegression analysisHypothesis testing

Subject Classifications

62J0562C05

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