Archives

• Nepal Journal of Statistics and Data Sciences

  Vol. 1 (2026)

  The journal covers a broad spectrum of topics including statistical theory and methods, applied statistics, data analytics, machine learning, artificial intelligence, big data, biostatistics, econometrics, computational statistics, survey methodology, official statistics, and interdisciplinary applications of data science across science, technology, health, economics, and social sciences etc. Its primary objective is to promote rigorous research, innovation, and practical applications in Statistics and Data Science, while serving as a strong academic platform for researchers from Nepal and the global community.

  • Perceived Service Quality and Students’ Satisfaction in a Higher Education Institution: A Structural Equation Modeling Approach — pages 1–9
  • Modeling and Forecasting Nepal's Nominal GDP with an Updated Box Jenkins ARIMA Analysis — pages 10–18
  • AI-Driven Productivity Impact Analysis Using GIS and IoT Data in Sugar Industries: A Pilot Study — pages 19–24
  • Natural Calamity Deaths in Nepal: Analysis of the 2021 National Population and Housing Census — pages 25–32
  • Modeling Minimum Wage Determination in Nepal: The Role of Economic Growth and Inflation — pages 33–38
  • Development of an Empirical Bayesian Single-Attribute Acceptance Sampling Plan for Food Quality using a Beta–Binomial Model
  • Structural Equation Modeling: A Review of Its History, Methods, and Applications — pages 50–58
  • Structural Modeling of Employee Performance: The Roles of Capacity Building and Supervisor Support in Nepalese Commercial Banks — pages 59–66