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“The workshop has been successfully culminated. Details of the workshop will be updated soon.”

Objective of the Predictive Analytics with R

The programme intends to introduce participants to the R software environment, Text Mining Analytics and Factor Analysis and SEM. Participants will get the requisite skills in formulating business and social problems, analyzing the problem and communicating the results effectively. At the end of the programme participants will be able to

1. Use R statistical software environment
2. Identify social and business problems where the predictive analytics tools that will be covered, can be applied.
3. Perform text mining and social media analytics using R
4. Apply Structural Equation Modelling for analytical research


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Objective of the Workshop

Qualitative data can often be seen as an embodied expression of human beings of anxieties, interests, hopes and tensions pertaining to a variety of social and organizational concerns. In comparison to quantitative data which is collected by enforcing responses where they may not naturally exist, qualitative data embodies an organic unraveling of phenomena. Even while analyzing data pertaining to corporations, quantitative data such as financial indicators may often represent a black box. What led to a particular financial outcome? What were the strategies, marketing practices and human resource mobilizations that led to these outcomes?

Who were the people involved in these processes and through what political interests and passions did they engage with each other? Qualitative data can throw light on a variety of these issues. However, the validity and generalizability of qualitative analysis has often been called into question. Content analysis is a technique for responding to the needs of validity and reliability in qualitative analysis. Content analysis represents a variety of techniques which can discern the underlying structures of qualitative data using statistical and coding methodologies.


Trial versions of software such as VBPro and Diction will be used to demonstrate the use of content analysis techniques.



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