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Data Science
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MEASURE Evaluation explored the potential of data science to strengthen health systems and improve monitoring and evaluation.
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Our Work
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Data Science Programming Library
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This page presents some examples of core R code for kriging and mapping that has been used by the project to support its work in geospatial analysis with big data for global health.
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Our Work
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Data Science
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Jupyter Notebooks FAQ
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Jupyter notebooks provide an opportunity to share not only executable code but also provide context about the code and the techniques used.
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Our Work
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Data Science
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Data Science Programming Library
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R Markdown FAQ
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R Markdown is a file format for R code that makes it possible to create shareable documents that include not only code but also text.
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Our Work
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Data Science
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Data Science Programming Library
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Defining Electronic Health Technologies and Their Benefits for Global Health Program Managers
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Our Work
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Health Information Systems
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Data Science for Global Health
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Lance P, Spencer J, Janko M (2016)
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Resources
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Publications
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Directives des réunions de revue des données: pour évaluer et améliorer la performance
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Eric Geers, Jonas Sagno, and Albert Camara (2017)
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Publications
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Linking Data from Demographic and Agricultural Surveys to Examine the Drivers of Stunting and Wasting in Nigeria: Lessons Learned
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Emily H. Weaver, Siân Curtis, John Spencer, Gustavo Angeles (2020)
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Resources
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Publications
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Data Science for Health Decision Making
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MEASURE Evaluation (2015)
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Resources
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Publications
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Defining Electronic Health Technologies and Their Benefits for Global Health Program Managers: Data Science and Big Data
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MEASURE Evaluation (2015)
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Resources
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Publications