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Effective and Ineffective Statistical Analysis Tools in Project Management Environments: A Real Life Study
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Author(s): Brian J. Galli (Department of Engineering, Hofstra University, Hempstead, USA)
Copyright: 2020
Volume: 10
Issue: 1
Pages: 17
Source title:
International Journal of Applied Logistics (IJAL)
Editor(s)-in-Chief: Lincoln C. Wood (University of Otago, New Zealand & Curtin University, Australia)
DOI: 10.4018/IJAL.2020010104
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Abstract
The study aims to investigate the effectiveness and ineffectiveness of different statistical analysis tools in project management environments. Furthermore, this study focuses on identifying some factors that affect project management by highlighting some commonly used statistical analysis tools and by evaluating ineffective analysis tools. Quantitative data was collected through participant observation, as well as a review of the relevant materials to meet these objectives. Some of the dependent variables that were tested in the study include the project manager's skills, the organization's financial status, and the affordability of the analysis tools. The independent variable is the effectiveness and ineffectiveness of the statistical analysis tools. After collecting and analyzing the data, the study finds that a tool's effectiveness or ineffectiveness depends on the dependent variables, i.e., the project managers' skills, the organization's financial status, etc.
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