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4. novembrī notiks RSU Doktorantūras skolas vebinārs Mastering your Data – from Exploration to Visualization / Data Wrangling I.

Darba valoda: angļu

Par lektoru

sergio_uribe.jpgProf Sergio Uribe is Lead Researcher of the RSU Bioinformatics Research Unit, Visiting Associate Professor at the RSU School of Dentistry, and Associate Professor at the Universidad Austral de Chile, Valdivia, Chile. Sergio has dedicated his life to scientific research investigating how to improve people's oral health, either through interventions, by identifying risk factors that can be modified or improving the diagnostic accuracy and usefulness of maxillofacial imaging tests.

Dr Uribe works with researchers from different countries and the results of their research have been disseminated in more than 50 publications in high impact journals and book chapters. He is Dentist and Specialist in Maxillofacial Radiology from the University of Valparaiso, Chile and PhD from the Universidad Austral de Chile, Valdivia, Chile. Tweet often at @sergiouribe

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Par kursu

The traditional approach to research programmes is to assume that students will find a way to analyse and visualise their data. This assumption brings problems for the students, their supervisors and a significant waste of time. Many students are scared by the data rather than curious and usually skip exploratory data analysis and go straight to advanced statistical models that they cannot explain later because they do not understand their data in depth. This course aims to provide basic knowledge, skills and tools to perform such an exploratory data analysis, with a major focus on publication-ready data visualisation to detect patterns and trends in the data, to extract meaningful information from the data and to prepare for further inferential analysis.

On successful completion of the course, the students will have the knowledge and practical skills to successfully apply the R statistical software and its essential functions and packages to wrangle and transform their research data to perform informative exploratory analyses and perform publication-ready visualisation of their data, enabling effective interpretation and communication of the research results and findings to the scientific community.

Course page and more information

Pieteikties

Nākamie vebināri šajā ciklā

20.11.Data Wrangling II
2.12.Data Management
18.12. Data Final project
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