R for ALL
Training is teaching, or developing in oneself or others, any skills and knowledge or fitness that relate to specific useful competencies. Training has specific goals of improving one's capability, capacity and intellectual insights. Teaching is more theoretical and abstract, while training (when done well) is more hands-on and practical. Teaching seeks to impart knowledge and provide information, while training is intended to develop abilities. Training and workshops are interactive sessions during which the audience, utilizing their laptops, will try out a new technology or learn a new skill or technique under the guidance of the workshop presenter or trainer. Our training is intended to raise awareness and develop skills of the audience about a software tool, library, and language of R. Our training, however, is subdivided into two sections: virtual (online webinar) and physical in form of symposium. Since 14th day of September, 2017 when the idea was conceived and official commission of Osun RUG was done, we have been active by practically promoting the use of R language through various training, symposium and workshops. Quite a number of webinars, where experts in the field of data science with R syntax are featured, have been conducted FREE OF CHARGE, courtesy of R Consortium as well as R Foundation and R Studio.
R for ALL
Statistical Computing with a generally accepted Software: R
To do data analysis is to do computing. Statisticians have always been heavy users of whatever computing facilities are available to them. As the computing facilities have become more powerful over the years, those facilities have obviously decreased the amount of effort the statistician must expend to do routine analyses. Also, as the computing facilities have become more powerful, an opposite result has occurred, however; the computational aspect of the statistician’s work has increased. This is because of paradigm shifts in statistical analysis that are enabled by the computer. Statistical analysis involves use of observational data together with domain knowledge to develop a model to study and understand a data-generating process. The data analysis is used to refine the model or possibly to select a different model, to determine appropriate values for terms in the model, and to use the model to make inferences concerning the process. This has been the paradigm followed by statisticians for centuries. The advances in statistical theory over the past two centuries have not changed the paradigm, but they have improved the specific methods. The advances in computational power have enabled newer and more complicated statistical methods. Not only has the exponentially-increasing computational power allowed use of more detailed and better models, however, it has shifted the paradigm slightly. Many alternative views of the data can be examined. Many different models can be explored. Massive amounts of simulated data can be used to study the model/data possibilities. When exact models are mathematically intractable, approximate methods, which are often based on asymptotics, or methods based on estimated quantities must be employed. Advances in computational power and developments in theory have made computational inference a viable and useful alternative to the standard methods of asymptotic inference in traditional statistics. Computational inference is based on simulation of statistical models. The ability to perform large numbers of computations almost instantaneously and to display graphical representations of results immediately has opened many new possibilities for statistical analysis. The hardware and software to perform these operations are readily available and are accessible to statisticians with no special expertise in computer science but only require training!. This is what our RUG is giving out FREE OF CHARGE!. To train interested ones the use and application of R syntax in handling data science related disciplines as well as machine learning algorithms with graphics and visualization.
R for ALL
Virtual Training (Webinar)
Our virtual training is almost every month unless otherwise there is another cogent event that may overlap its monthly occurrence. On monthly basis, we pay zoom with a view to having access to zoom link for the webinar. For each of these virtual trainings, we generate zoom link every time of need and generate registration link via Google drive for all the intending participants to get registered after which the generated zoom link is shared via email and some other social media platforms like WhatsApp, twitter, telegram and so on. One of the recently conducted webinars was advertised by the R Consortium with the following link:
Flyers of some of the recently conducted online webinars are shown below:
R for ALL
With supports from the R Consortium as well as R Studio (and R Foundation), we periodically conduct physical trainings, which involve sending out posters and flyers and intending participants are chosen randomly. On many occasions, we usually collaborate with academic institutions for the conduct of physical trainings on the use of R language to handle statistical computing and mathematically-inclined issues arising from different perspectives of human endeavours. However, Osun RUG has conducted not less than fifteen physical training across the continent of Africa. We preach the gospel of R to almost everyone in need free of charge. We spread the news about R everyday within and outside our locality. We are committed teams of enthusiastic minds who are passionate to go miles in ensuring that younger ones know, use and even spread the good news about R language while performing their statistical operations at all levels across the length and breadth of African continent. See photographs taken at some of the physical trainings we had in the recent times: