Analytics and Statistical Modelling in R for Beginners is an 6-week foundational course that highlights the growing importance of R software as a core analytical skill in academics and research. In today’s data-driven academic environment, proficiency in R is increasingly expected from students, research scholars, and faculty members for projects, coursework, dissertations, funded projects, and publications in high impact journals. R has become a global standard due to its open-source nature, advanced statistical capabilities, extensive libraries, and ability to generate publication-ready outputs. In fact, R is known for its statistical computing. This course equips learners especially postgraduate students, MPhil/PhD scholars, and academicians with the essential skills to analyze real-world datasets and perform statistical modelling using R. Beginning with the basics of R and RStudio, the course gradually introduces data import, data wrangling, exploratory analytics, hypothesis testing, and regression modelling. Practical demonstrations and guided hands-on exercises ensure that even first-time users of R gain confidence in working with data.
A unique strength of this course is its focus on research-oriented interpretation and reporting. Learners will not only apply analytical methods but also learn to convert their results into academic tables, graphs, and narratives suitable for theses, research articles, and conference presentations. By the end of eight weeks, participants will be able to execute a complete data analysis workflow from raw dataset to structured research output making this course highly valuable for academic progression, scholarly publications, and evidence-based decision making in the social science and management domains.
