Structure of Rabindrik human values

Abstract

Principal component analysis is probably the oldest and best known of the techniques of multi variate analysis. It was first introduced by Pearson (1901), and developed independently by Hotelling (1933). The central idea of principal component analysis is to reduce the dimensionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semi definite symmetric matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique hasa wide variety of different applications, as well as a number of different derivations and here we demonstrate it for gaining important insights on Rabindrik values.MethodParticipantsIt is widely claimed that the diversity factor is one of the major reason for promotion of learning at an institute like that of HM. In such an environment it is useful to understand in what factors the population differs at an IIM, what are the major factors of differentiation and if we can classify them into logical sets with reduced dimensions. The factors which we considered for our study were data collected on Rabindrik values which are collection of attributes referring to the way of self-awakening through the use of therapeutic postulates extracted from the literary works of Rabindranath Tagore. Here based on the set of the attributes for which data is collected on a Likert scale of 1-14 the attributes were ranked from most desirable to least desirable. PC A analysis was then performed on the attributes to identify reduced groups of attributes which can be used to represent the varied population analyzed with minimum loss of variance. SPSS was used as a tool for performing the analysis which makes it easy as the tests for necessary prerequisites are also performed automatically in the tool. The steps to perform the analysis in SPSS can be summarized in the steps as below. This is done in order to allow the users of the paper to reproduce the results at a later point in time. Of the data collected for the 28 variables the first 14 variables viz.Self-awakening, emotional control, systematic, self-insulating less, fearless, cleanliness, no work-family conflict, niskam principle, challenging, self-understanding, doubtless, free from fear of failure, resolute, active are measuring path oriented human values whereas the remaining 14 variables, i.e., Peace, universalization, Enlightenment, positive feeling, family security, Sense of Accomplishment, Pleasure, Inner harmony, Self-Respect, Salvation, Self-Empowerment, Security, Significance in Life and Altruism are goal oriented human values. The steps followed for analysis for either group would be same but the analysis would be performed separately for both groups as both are measuring different attributes viz. the path andthe goal. We would begin with the reliability analysis for the data and we would be using the Cronbach's Alpha for the same.Data collection and exploratory analysisThe data for the effort was collected from the participants of the PGP and FPM program of Indian Institute of Management, Shillong for the academic year of 2013-14 and 2014-15. The data was collected through an online google form before which an explanation about the purpose and use of data was communicated to both the batches through formal sessions. This was a necessary step as some of the path and goal variables may not be clear to the participants which may led to data inconsistency. The participants were advised to fill the data form at their own convenience in a time gap of about five to seven days so that they could understand self and then fill the requisite information. …