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 modelling and factor analysis, with a clear focus on transparency and responsible inference.
Key features include:
· A structured pathway from statistical foundations to advanced quantitative techniques used across digital social research.
· Practical guidance on modelling and inference, including linear and logistic regression, multivariate methods, and factor analysis.
· Coverage of common pitfalls in interpretation and reporting, including p-values, uncertainty, and claims that overreach the evidence.
· An open science and reproducibility lens, with emphasis on clear documentation of data preparation and analytic choices.
· A platform-neutral approach that supports readers working across software packages and coding environments.
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 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.
Introduction,
1. Descriptive Statistics and Exploratory Data Analysis,
2. Fundamentals of Statistical Inference and Hypothesis Testing,
3. Comparing
Group Means t-Tests and ANOVA,
4. Correlation and Simple Linear Regression,
5. Multiple Linear Regression and Model Building,
6. Logistic Regression and
Generalized Linear Models,
7. Non-Parametric and Robust Statistical Methods,
8. Exploratory Factor Analysis and Principal Component Analysis,
9.
Confirmatory Factor Analysis and Structural Equation Modeling,
10.
Conclusion,
11. References
ukasz Sukowski 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. He also leads the Department of Higher Education Institutions Management at Jagiellonian University and works as President of Management Board of Polish division in Public Consulting Group (PCG Holding).
Maria Rybaczewska
is an assistant professor and researcher specializing in marketing and trade, with a PhD from Lodz University of Technology. Her work focuses on consumer behavior, retail and convenience sectors, and the resilience of these markets, combining academic research with business consulting experience in Poland and internationally.
Katarzyna Szczepaska-Woszczyna
holds a postdoctoral degree in economic sciences and is a professor, Vice-Rector for Science and Education, and Dean of the Faculty of Applied Sciences at WSB University. She is the author or co-author of over 120 publications and serves on the "Excellent Science" board at the Ministry of Science and Higher Education (Poland) and as a member of the Polish Accreditation Committee.
