Three Days R Workshop



We often seek to explain the real-world phenomena (i.e., behavior of interest rates in the economic markets, behavior of consumers in purchasing products or behavior of students at the end of exam party, etc.) by collecting data from the real worlds, and the using these data to draw conclusion about what is being studied. But very often, the implications of the data are not so obvious, especially when we have collected a large amount of data in numeric form. Simply looking at lots of numbers is usually uninformative and possibly confusing. Data analysis is a body of methods that help to describe facts, detect patterns, develop explanations, and test hypotheses. A mass of data can be described and summarized or different sets of data can be compared by the calculation of appropriate statistics. But since time immemorial, students have despised statistics. For one thing, most have a non mathematical background, which makes understanding complex statistical equation very difficult!!! Today, the major advantage in learning statistics is considerably easier because of the development of statistical packages.

R is one such a powerful, open-source programming language for the statistical analysis of data. R is widely used computer-based software for students and researchers in the field of management, social science, psychology, sociology, psychiatry, and other behavioral sciences. It does an extensive range of both univariate and multivariate procedures used in these disciplines. The R programming language is used for data analysis, data manipulation, graphics, statistical computing and statistical analysis. In short, R is a sophisticated piece of open source software used by social scientists and related professionals for statistical analysis.

Objectives of Workshop 

The main objective of this workshop is to provide hands on training in understanding the concepts in data science and statistical analysis using R. This workshop is to give brief and straightforward descriptions of how to conduct a range of statistical analyses using R.

At the end of the workshop, participants should be able to:

  • Get hands-on practice that will develop an understanding of the way R works.
  • Know how to select an appropriate test and how to perform statistical calculations in step-by-step manner using R.  
  • Gets knowledge about how to represent data using Graphs in R.
  • Explore how to analyze research data using R


Important Note:

We hope that even participants who have limited or no statistical background will still be able to undertake appropriate analyses of their data. Case based learning method will be used to fulfill the objectives of the workshop.

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