TNAU Hosts Five-Day Workshop on Data Analysis and Visualization with R-Programming

Tamil Nadu Agricultural University in Coimbatore is conducting a five-day hands-on training on data analysis and visualization using R-programming from July 29 to August 2, 2024, for teachers, students, and researchers from various institutions.


Coimbatore: The Department of Plant Molecular Biology and Bioinformatics under the Directorate of Plant Molecular Biology and Biotechnology Centre at Tamil Nadu Agricultural University (TNAU) is organizing a five-day hands-on training workshop on data analysis and visualization using R-programming. The workshop is scheduled to run from July 29 to August 2, 2024.

Participants from various educational and research institutions have been selected for this training, including representatives from Kolathur Research Farm, Bangalore; Providence Women's College, Kozhikode; Kaamadhenu Arts and Science College, Krishnankoyil; ICAR-Sugarcane Breeding Institute; and Tamil Nadu Agricultural University.



The training program commenced with a welcome address by Dr. A. John Joel, Professor and Head of the Department of Plant Molecular Biology and Bioinformatics. He emphasized the importance of data analysis and R-programming in research. Following this, participants introduced themselves.

Dr. T. Suresh Kumar, Director of the Centre for Agricultural and Rural Development Studies and Dean of the School of Post Graduate Studies, delivered a felicitation address. He highlighted the significance of data analysis using R, shared his personal research experiences, and discussed the crucial role of data analysis in research.

The inaugural session concluded with a vote of thanks by Dr. E. Kokiladevi, Professor and Head of the Department of Plant Molecular Biology and Biotechnology. Assistant Professors Dr. N. Saranya (Bioinformatics), Dr. Santosh Ganapati Patil (Statistics), and Dr. T.T. Divyaprabha (Project Scientist) are conducting the R-programming training sessions.

The workshop focuses on R-programming fundamentals, data interfaces, R packages, basic statistical concepts, correlation, association, regression, chi-squared test, ANOVA, and other fundamental statistical analyses. Participants are receiving hands-on training in R-programming with a specific emphasis on data analysis techniques.

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