SNRI

(ICMSMAS - 27) | Hybrid Event
27th - 28th January 2027 | Ottawa, Canada

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International Conference on Multivariate Statistical Methods in Applied Sciences
(ICMSMAS - 27)

27th - 28th January 2027 Ottawa, Canada (Hybrid Event)

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Call for Paper

The ICMSMAS is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Statistics, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Multivariate statistical methods overview
  • Applications of multivariate analysis in research
  • Multivariate methods in health sciences
  • Statistical techniques for high-dimensional data
  • Multivariate regression analysis advancements
  • Principal component analysis applications
  • Factor analysis in social sciences
  • Cluster analysis and its applications
  • Multivariate methods in finance
  • Canonical correlation analysis techniques
  • Multivariate time series analysis
  • Ethics in multivariate statistical research
  • Applications of multivariate methods in marketing
  • Multivariate methods for environmental data
  • Statistical challenges in multivariate analysis
  • Multivariate analysis in machine learning
  • Recent developments in multivariate statistics
  • Multivariate methods in education research
  • Statistical software for multivariate analysis
  • Future directions in multivariate research
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

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