Quantitative Methods of Research in Digital Landscape equips social science and management researchers to design, run, and interpret statistical analyses for today's data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modeling and factor analysis, with a clear focus on transparency and responsible inference.
Written for PhD and Master's students, advanced undergraduates, early-career researchers, and practitioners who work with social data in fields such as sociology, management, communication, education, public policy, and media studies, it supports methods training and applied research projects in the digital age.
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¿ukasz Su¿kowski is a professor of economic sciences and humanities specializing in higher education management, social science methodology, HRM, and organizational culture, and serves as President of WSB University.
Marta Pikiewicz is an early-career researcher affiliated with WSB University, whose work focuses on sustainable development, organisational value creation, and management in contemporary organisations, with contributions to research on ESG practices in the IT sector.
Katarzyna Szczepäska-Woszczyna holds a postdoctoral degree in economic sciences and is a Vice-Rector for Research and Education at WSB University, specializing in management and quality sciences, with a focus on HRM, innovation, knowledge transfer, and sustainability
This book equips social science and management researchers to design, run, and interpret statistical analyses for today’s data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modelling and factor analysis, with a clear focus on transparency and responsible inference.
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Hardcover. Zustand: new. Hardcover. Quantitative Methods of Research in Digital Landscape equips social science and management researchers to design, run, and interpret statistical analyses for todays data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modeling and factor analysis, with a clear focus on transparency and responsible inference.Written for PhD and Masters students, advanced undergraduates, early-career researchers, and practitioners who work with social data in fields such as sociology, management, communication, education, public policy, and media studies, it supports methods training and applied research projects in the digital age. This book equips social science and management researchers to design, run, and interpret statistical analyses for todays data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modelling and factor analysis, with a clear focus on transparency and responsible inference. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781041339434
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Hardcover. Zustand: new. Hardcover. Quantitative Methods of Research in Digital Landscape equips social science and management researchers to design, run, and interpret statistical analyses for todays data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modeling and factor analysis, with a clear focus on transparency and responsible inference.Written for PhD and Masters students, advanced undergraduates, early-career researchers, and practitioners who work with social data in fields such as sociology, management, communication, education, public policy, and media studies, it supports methods training and applied research projects in the digital age. This book equips social science and management researchers to design, run, and interpret statistical analyses for todays data-rich research environment, from core descriptive statistics and hypothesis tests through to regression modelling and factor analysis, with a clear focus on transparency and responsible inference. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9781041339434
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