Quantitative research
Label
Quantitative research
Name
Quantitative research
Actions
Incoming Resources
- Handbook of research methods and applications in empirical finance, edited by Adrian R. Bell, Chris Brooks and Marcel Prokopczuk
- Data driven decisions, a practical toolkit for librarians and information professionals, Amy Stubbing
- Interpretive quantification, methodological explorations for critical and constructivist IR, J. Samuel Barkin and Laura Sjoberg, editors
- Educational Data Analytics for Teachers and School Leaders, by Sofia Mougiakou, Dimitra Vinatsella, Demetrios Sampson, Zacharoula Papamitsiou, Michail Giannakos, Dirk Ifenthaler
- Information Retrieval in Bioinformatics, A Practical Approach, edited by Soumi Dutta, Saikat Gochhait
- Novel Mathematics Inspired by Industrial Challenges, edited by Michael Günther, Wil Schilders
- Foundations of agnostic statistics, Peter M. Aronow, Benjamin T. Miller
- Event Attendance Prediction in Social Networks, by Xiaomei Zhang, Guohong Cao
- Researching religion, why we need social science, Steve Bruce
- Models for Data Analysis, SIS 2018, Palermo, Italy, June 20-22, edited by Eugenio Brentari, Marcello Chiodi, Ernst-Jan Camiel Wit
- Data Analytics Applications in Emerging Markets, edited by José Antonio Núñez Mora, M. Beatriz Mota Aragón
- Model identification and data analysis, Sergio Bittanti
- Ten Projects in Applied Statistics, by Peter McCullagh
- Mechanistic Data Science for STEM Education and Applications, by Wing Kam Liu, Zhengtao Gan, Mark Fleming
- Applied data analytics, principles and applications
- Be data literate, the data literacy skills everyone needs to succeed, Jordan Morrow
- An Introduction to Statistics with Python, With Applications in the Life Sciences, by Thomas Haslwanter
- Analyzing quantitative data, an introduction for social researchers, Debra Wetcher-Hendricks
- Harvard data science review, HDSR : a microscopic, telescopic, and kaleidoscopic view of data science, Harvard Data Science Initiative
- Data analytics, concepts, techniques, and applications, edited by Mohiuddin Ahmed and Al-Sakib Khan Pathan
- Utilization of Geospatial Information in Daily Life, Expression and Analysis of Dynamic Life Activity, edited by Yoshihide Sekimoto, Yasuhiro Kawahara
- Applied Statistics and Data Science, Proceedings of Statistics 2021 Canada, Selected Contributions, edited by Yogendra P. Chaubey, Salim Lahmiri, Fassil Nebebe, Arusharka Sen
- Handbook of Statistical Bioinformatics, edited by Henry Horng-Shing Lu, Bernhard Schölkopf, Martin T. Wells, Hongyu Zhao
- Strategic analytics
- Quantitative techniques in business, management and finance, a case-study approach, Umeshkumar Dubey, D P Kothari, G K Awari
- Q-squared, combining qualitative and quantitative approaches in poverty analysis, Paul Shaffer
- Best practices in data cleaning, a complete guide to everything you need to do before and after collecting your data, Jason W. Osborne
- Generalized linear models for bounded and limited quantitative variables, Michael Smithson, Yiyun Shou
- How Data Quality Affects our Understanding of the Earnings Distribution, by Reza Che Daniels
- Survey scales, a guide to development, analysis, and reporting, Robert L. Johnson, Grant B. Morgan
- Statistics Applied With Excel, Data Analysis Is (Not) an Art, by Franz Kronthaler
- Econometrics and data science, apply data science techniques to model complex problems and implement solutions for economic problems, Tshepo Chris Nokeri
- Regression models for categorical and count data, Peter Martin
- Legal analytics, the future of analytics in law, edited by Namita Singh Malik, Elizaveta A Gromova, Smita Gupta and Balamurugan Balusamy
- Quantitative methods, for business, management and finance, Louise Swift and Sally Piff
- Machine learning for big data analyis, edited by Siddhartha Bhattacharyya, Hrishikesh Bhaumik, Anirban Mukherjee, Sourav De
- Studies in Theoretical and Applied Statistics, SIS 2021, Pisa, Italy, June 21-25, edited by Nicola Salvati, Cira Perna, Stefano Marchetti, Raymond Chambers
- Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management, edited by Dinesh K. Sharma, Madhu Jain
- Mathematical and Computational Intelligence to Socio-scientific Analytics and Applications, edited by Pankaj Srivastava, M. Lellis Thivagar, Georgia Irina Oros, Chai Ching Tan
- Data science foundations, geometry and topology of complex hierarchic systems and big data analytics, Fionn Murtagh
- Writing up quantitative research in the social and behavioral sciences, Marianne Fallon
- Theory and credibility, integrating theoretical and empirical social science, Scott Ashworth, Christopher R. Berry, Ethan Bueno de Mesquita
- Handbook of quantitative research methods in entrepreneurship, edited by George Saridakis, Marc Cowling
- Object oriented data analysis, J.S. Marron and Ian L. Dryden
- Méthodes qualitatives, quantitatives et mixtes, dans la recherche en sciences humaines, sociales et de la santé, sous la direction de Marc Corbière et Nadine Larivière
- Best practices in quantitative methods, edited by Jason W. Osborne
- Introduction to data mining and analytics with machine learning in R and Python, Kris Jamsa
- Q-squared, combining qualitative and quantitative approaches in poverty analysis, Paul Shaffer
- Practical propensity score methods using R, Walter Leite
- Data analytics, a small data approach, Shuai Huang & Houtao Deng
Outgoing Resources
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