For the full blog, please see the website of Clima-LoCa
From 12 to 15 February, we were immersed in a training on data analysis and experimental design at R Studio, offered within the framework of the objectives of the Clima-LoCa project. Participants from different universities and countries were encouraged to take part in a short but substantial learning program.
During the capacitation days fundamental concepts of data analysis and advanced experimental design techniques were addressed, as well as their practical implementation using R Studio. Collaboration was encouraged among participants, who shared knowledge and experiences from their respective academic and cultural fields.
Among the participants, the dialogue was promoted to enrich the discussion and understanding of the topics. The diversity of perspectives allowed a broader and more global view of data analysis, showing how different contexts can influence the interpretation and application of statistical techniques.
In addition, there was the contribution of Professor Aquiles Darghan who currently works as an associate professor and senior researcher at the Universidad Nacional of Colombia, and whose contribution was key in the transmission of knowledge related to statistical data. His participation allowed attendees to explore new functionalities and advanced techniques in R Studio, expanding their skills set and knowledge. Experimental designs were also worked on cocoa based on cadmium (Cd), all within the framework of the project «Clima Loca».
Emphasis was also placed on the ethics of data analysis, discussing the importance of integrity and transparency at all stages of the research process. Topics such as data manipulation, proper use of statistics and honest presentation of results were addressed, highlighting the responsibility of researchers in the interpretation and communication of findings.
At the end, attendees not only acquired solid foundations in data analysis and experimental design, but also developed a broader understanding of the use of R Studio as a powerful tool for scientific research.
