Authors : Adegbite Joseph S.

Volume/Issue : Volume 11 - 2026, Issue 4 - April

Google Scholar : https://tinyurl.com/yaer9c6f

Scribd : https://tinyurl.com/mprbyv26

DOI : https://doi.org/10.38124/ijisrt/26apr1198

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The persistence of human problems across health, industrial, and social sectors often stems not from lack of resources but from decisions made without empirical evidence. This study investigates the extent to which statistical knowledge influences the identification, analysis, and resolution of human problems. Anchored in Deming’s Theory of Profound Knowledge and the Evidence-Based Practice framework, the research employs a mixed-methods approach combining systematic literature review and multiple case studies from Nigeria and global contexts. Five core statistical competencies were identified as critical for non-specialists: descriptive summarization, variation analysis, prioritization via Pareto analysis, hypothesis testing, and predictive modeling. Case data from (1) a Lagos manufacturing plant, (2) a primary healthcare centre in Ibadan, and (3) a World Bank community project were analyzed. Results demonstrate that interventions guided by basic statistical analysis achieved 43-78% higher success rates than intuition-based approaches, with mean cost savings of 36.2% (SD=11.4). Control chart implementation reduced process defects from 8.4% to 2.9% in 10 weeks, p<0.01. Hypothesis testing of staff intervention reduced absenteeism by 41%, statistically significant at α=0.05. The study concludes that statistical literacy is a high-leverage determinant of problem-solving efficacy. The major constraint is not mathematical complexity but organizational culture and training gaps. A “5Q Framework” is proposed for workplace adoption. The thesis recommends integrating statistical thinking into MSc, MBA, and professional curricula, and mandating data review before capital expenditures above ₦5 million.

Keywords : Statistical Literacy, Evidence-Based Management, Problem Solving, Deming, Pareto Analysis, Nigeria.

References :

1. American Statistical Association. (2016). _Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report_. ASA.
2. Antony, J., et al. (2017). A systematic review of Six Sigma in SMEs. _International Journal of Quality & Reliability Management, 34_(7), 1070-1091. https://doi.org/10.xxxx
3. Banerjee, A. V., & Duflo, E. (2011). _Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty_. PublicAffairs.
4. Creswell, J. W. (2014). _Research Design: Qualitative, Quantitative, and Mixed Methods Approaches_ (4th ed.). Sage.
5. Deming, W. E. (1994). _The New Economics for Industry, Government, Education_ (2nd ed.). MIT Press.
6. Gal, I. (2002). Adults’ statistical literacy: Meanings, components, responsibilities. _International Statistical Review, 70_(1), 1-25.
7. Mayer-Schönberger, V., & Cukier, K. (2013). _Big Data: A Revolution That Will Transform How We Live, Work, and Think_. Houghton Mifflin.
8. Montgomery, D. C. (2019). _Introduction to Statistical Quality Control_ (8th ed.). Wiley.
9. Musa, S., et al. (2020). Use of run charts to reduce drug stock-outs in Kaduna PHCs. _Nigerian Journal of Health Sciences, 20_(2), 45-51.
10. National Bureau of Statistics. (2023). _Statistical Literacy Baseline Survey Nigeria_. NBS.
11. Pfeffer, J., & Sutton, R. I. (2006). _Hard Facts, Dangerous Half-Truths, and Total Nonsense: Profiting from Evidence-Based Management_. Harvard Business Review Press.
12. Rosling, H., Rosling, O., & Rönnlund, A. R. (2018). _Factfulness: Ten Reasons We're Wrong About the World_. Flatiron Books.
13. Sackett, D. L., et al. (1996). Evidence based medicine: What it is and what it isn’t. _BMJ, 312_(7023), 71-72.
14. Wheeler, D. J. (2000). _Understanding Variation: The Key to Managing Chaos_. SPC Press.
15. World Health Organization. (2022). _Score for Health Data Technical Package_. WHO.