The School of Nuclear and Allied Sciences (SNAS) of the University of Ghana has held a five-day workshop in Accra for undergraduate and graduate students in Physics on how to use ‘R Programming’ for Statistical Inference, Data Analysis and Machine Learning Algorithms.
‘R Programming’ is a type of statistical software that assists researchers in collecting and analysing data to provide science-based insights into patterns and trends.
Addressing participants at the closing ceremony, the Director General of GAEC, Prof. Samuel Boakye Dampare, explained that research scientists collect large amounts of data that must be analysed and standardised, which the R Programming assists with. “R Programming provides a number of tools that significantly simplify the process of preparing data for analysis,” he said.
Prof. Dampare further explained that the software has an extremely useful function that displays data before one starts any analysis. “You can see your data in a matter of seconds and gain insights that tabular data alone cannot provide,” he added.
According to Prof. Dampare, the use of R Programming in business analysis has gained a lot of traction in recent years as businesses increasingly rely on data analytics to help them gain insights into business issues and solve problems.
“R Programming is no longer just for academics and research; it is now used in a wide range of industries, including IT, finance, healthcare, and many others,” he said.
Prof. Dampare commended the participants for availing themselves, and urged them to apply what they had learned in their studies and respective fields.
The five-day workshop was organised in collaboration with the National Nuclear Research Institute (NNRI) of GAEC and funded by the International Centre for Theoretical Physics (ICTP). Certificates of participation were presented to participants.
Topics covered include: Introduction to R Programming, R Studio and Installation, Introduction to core programming principles, Import and export of raw data files, Computing numerical statistics in R, and Data analysis and presentation in R, among others.