8 resultados para Qualitative data analysis software
em University of Washington
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Thesis (Ph.D.)--University of Washington, 2016-08
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Thesis (Master's)--University of Washington, 2016-06
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This mixed-methods study analyzed quantitative and qualitative data on rental market conditions in the Seattle area, their effects on renters, and coping mechanisms used by renters. Data was collected from 111 individuals using an online survey and face-to-face interviews. While the focus of the study was on low-income renters and other marginalized populations, results show that a majority of renters surveyed are struggling to make ends meet, and that rental market conditions are impacting renters’ residential situations, as well as their life choices in other areas, such as education, their career, and decisions to have children. Future research should investigate these relationships further and in more detail, particularly for renters from marginalized populations, and investigate what types of solutions or improvements renters would like to see.
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-06
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Thesis (Ph.D.)--University of Washington, 2016-08
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Scientific research is increasingly data-intensive, relying more and more upon advanced computational resources to be able to answer the questions most pressing to our society at large. This report presents findings from a brief descriptive survey sent to a sample of 342 leading researchers at the University of Washington (UW), Seattle, Washington in 2010 and 2011 as the first stage of the larger National Science Foundation project “Interacting with Cyberinfrastructure in the Face of Changing Science.” This survey assesses these researcher’s use of advanced computational resources, data, and software in their research. We present high-level findings that describe UW researchers’: demographics, interdisciplinarity, research groups, data use, software and computational use—including software development and use, data storage and transfer activities, and collaboration tools, and computing resources. These findings offer insights into the state of computational resources in use during this time period as well as offering a look at the data intensiveness of UW researchers.