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portada Sustainable Statistical and Data Science Methods and Practices. Reports from LISA 2020 Global Network, Ghana, 2022
Type
Physical Book
Collection
STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health
Year
2025
Pages
415
Format
Paperback
Dimensions
23.5x15.5 cm
ISBN13
9783031413544

Sustainable Statistical and Data Science Methods and Practices. Reports from LISA 2020 Global Network, Ghana, 2022

Eric A. Vance;O. Olawale Awe (Author) · Springer International Publishing AG · Paperback

Sustainable Statistical and Data Science Methods and Practices. Reports from LISA 2020 Global Network, Ghana, 2022 - Eric A. Vance;O. Olawale Awe

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Synopsis "Sustainable Statistical and Data Science Methods and Practices. Reports from LISA 2020 Global Network, Ghana, 2022"

This volume gathers papers presented at the LISA 2020 Sustainability Symposium in Kumasi, Ghana, May 2–6, 2022. They focus on sustainable methods and practices of using statistics and data science to address real-world problems. From utilizing social media for statistical collaboration to predicting obesity among rural women, and from analyzing inflation in Nigeria using machine learning to teaching data science in Africa, this book explores the intersection of data, statistics, and sustainability. With practical applications, code snippets, and case studies, this book offers valuable insights for researchers, policymakers, and data enthusiasts alike. The LISA 2020 Global Network aims to enhance statistical and data science capability in developing countries through the creation of a network of collaboration laboratories (also known as “stat labs”). These stat labs are intended to serve as engines for development by training the next generation of collaborative statisticians and data scientists, providing research infrastructure for researchers, data producers, and decision-makers, and enabling evidence-based decision-making that has a positive impact on society. The research conducted at LISA 2020 focuses on practical methods and applications for sustainable growth of statistical capacity in developing nations.

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