Please use this identifier to cite or link to this item:
192.168.6.56/handle/123456789/55645
Title: | Statistical Methods in Social Science Research |
Authors: | S. P. Mukherjee Bikas K. Sinha Asis Kumar Chattopadhyay |
Keywords: | Science Research |
Issue Date: | 2018 |
Publisher: | Springer |
Description: | To a large extent, social science research involves human beings and their groups and associated abstract entities like perception, attitude, personality, analytical skills, methods of teaching, evaluation of performance, merger of cultures, convergence of opinions, extinction or near extinction of a tribe. On the other hand, research in ‘hard sciences’ like physics, chemistry, or biotechnology involves largely concrete entities and their observable or measurable features. Social science is a big domain that encompasses psychology, social anthropology, education, political science, economics, and related subjects which have a bearing on societal issues and concerns. Currently, topics like corporate social responsibility (CSR), knowledge management, management of talented or gifted students, leadership, and emotional intelligence have gained a lot of importance and have attracted quite a few research workers. While we have ‘special’ schools for the mentally challenged children, we do not have mechanisms to properly handle gifted or talented children. While encompassing economics and political science within its ambit, social science research today challenges many common assumptions in economic theory or political dogmas or principles. Some of the recent research is focused on the extent of altruism—as opposed to selfish motives—among various groups of individuals. There has been a growing tendency on the part of social science researchers to quantify various concepts and constructs and to subsequently apply methods and tools for quantitative analysis of evidences gathered to throw light on the phenomena being investigated. While this tendency should not be discouraged or curbed, it needs to be pointed out that in many situations such a quantification cannot be done uniquely and differences in findings by different investigators based on the same set of basic evidences may lead to completely unwarranted confusion. |
URI: | http://10.6.20.12:80/handle/123456789/55645 |
ISBN: | 978-981-13-2146-7 |
Appears in Collections: | Population Studies |
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