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Statistical Methods in Social Science Research


Statistical Methods in Social Science Research



von: S P Mukherjee, Bikas K Sinha, Asis Kumar Chattopadhyay

CHF 94.50

Verlag: Springer
Format: PDF
Veröffentl.: 05.10.2018
ISBN/EAN: 9789811321467
Sprache: englisch

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Beschreibungen

This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research. The social sciences cover diverse phenomena arising in society, the economy and the environment, some of which are too complex to allow concrete statements; some cannot be defined by direct observations or measurements; some are culture- (or region-) specific, while others are generic and common. Statistics, being a scientific method – as distinct from a ‘science’ related to any one type of phenomena – is used to make inductive inferences regarding various phenomena. The book addresses both qualitative and quantitative research (a combination of which is essential in social science research) and offers valuable supplementary reading at an advanced level for researchers.
1. Introduction.- 2. Randomized Response Technique.- 3. Content Analysis.- 4.Scaling Techniques.- 5.Data Integration.- 6. Dis-agreement  vs. Agreement.- 7. Meta Analysis.- 8. Cluster and Discriminant  Analysis.- 9. Principal Component Analysis.- 10. Factor Analysis.- Multidimensional Scaling.- 11. Social and Occupational Mobility.- 12. Social Network Analysis.
<p>Shyama Prasad Mukherjee retired as the Centenary Professor of Statistics at Calcutta University, where he was involved in teaching, research and promotional work in the areas of statistics and operational research for more than 35 years. He was the Founder Secretary of the Indian Association for Productivity, Quality and Reliability and is now its Mentor. He received the Eminent Teacher Award [2006] from Calcutta University, P.C. Mahalanobis Birth Centenary Award from the Indian Science Congress Association [2000] and Sukhatme Memorial Award for Senior Statisticians from the Government of India [2013]. A Fellow of the National Academy of Sciences of India, Professor Mukherjee has about 80 research papers to his credit. He was a Vice-President of the International Federation of Operational Research Societies (IFORS ).</p>

Bikas Kumar Sinha was affiliated to the Indian Statistical Institute (ISI), Kolkata, India for more than 30 years until his retirement in 2011. He has travelled extensively within USA and Europe for collaborative research and teaching assignments. He has more than 140 research articles published in peer-reviewed journals and almost 100 research collaborators worldwide. His research interests cover a wide range of theoretical and applied statistics. He has co-authored three volumes on Optimal Designs in Springer’s <i>Lecture Notes Series in Statistics</i> (Vol. 54 in 1989, Vol. 163 in 2002 and Vol. 1028 in 2014) and another volume on theory and applications of Optimal Covariate Designs, also published by Springer (2015).<p></p>

Asis Kumar Chattopadhyay is a Professor of Statistics at Calcutta University, Kolkata, India, from where he also obtained his PhD in Statistics. With over 50 papers in respected international journals, proceedings and edited volumes, he has published three books on statistics including two published by Springer – ‘Statistical Methods for Astronomical Data Analysis’ (<i>Springer Series in Astrostatistics</i>, 2014) and ‘Statistics and its Applications: Platinum Jubilee Conference, Kolkata, India, December 2016’ (<i>Springer Proceedings in Mathematics & Statistics</i>, 2018). His main interests are in stochastic modeling, demography, operations research and astrostatistics.<p></p><p></p>
This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research. The social sciences cover diverse phenomena arising in society, the economy and the environment, some of which are too complex to allow concrete statements; some cannot be defined by direct observations or measurements; some are culture- (or region-) specific, while others are generic and common. Statistics, being a scientific method – as distinct from a ‘science’ related to any one type of phenomena – is used to make inductive inferences regarding various phenomena. The book addresses both qualitative and quantitative research (a combination of which is essential in social science research) and offers valuable supplementary reading at an advanced level for researchers.
Considers recent problems in social science research, for example social and occupational mobility Provides modern methods and tools for the analysis of data, like analysis of agreement, and multi-dimensional scaling Supplements theoretical discussions with worked examples from social science research problems
<p>Considers recent problems in social science research, for example social and occupational mobility&nbsp;</p><p>Provides modern methods and tools for the analysis of data, like analysis of agreement, and multi-dimensional scaling</p><p>Supplements theoretical discussions with worked-out examples from social science research problems</p>

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