SNRI

(ICESDAT - 27) | Hybrid Event
28th - 29th June 2027 | Saskatoon, Canada

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+91 9344546233 | [email protected]

International Conference on Experimental Statistics and Data Analysis Techniques
(ICESDAT - 27)

28th - 29th June 2027 Saskatoon, Canada (Hybrid Event)

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Call for Paper

The ICESDAT 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:

  • Innovative techniques in experimental statistics
  • Data visualization methods for analysis
  • Bayesian approaches in data analysis
  • Statistical methods for big data
  • Sampling techniques in experimental design
  • Statistical software for data analysis
  • Multivariate analysis in experimental research
  • Statistical inference in experimental studies
  • Applications of experimental statistics
  • Challenges in data collection methods
  • Ethics in experimental data analysis
  • Meta-analysis in experimental statistics
  • Time series analysis in experiments
  • Statistical quality control techniques
  • Experimental design for clinical trials
  • Data mining techniques in statistics
  • Machine learning in experimental research
  • Statistical modeling for social sciences
  • Causal inference in experimental studies
  • Statistical education and training initiatives
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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