Why Statistics is Not Data Science Chris Malone | Tisha Hooks
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What is Data Science? |
0: | The science of planning for, acquisition, management, analysis of, and inference from data (Source: StatSNSF Committee) |
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1: | Computational tools required for big/wide data
Non-traditional techniques used to analyze the data/create predictions - neural networks, machine learning, etc. |
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2: | "The art and science of computing with data???" |
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3: | Study and practice of the collection, maintenance, analysis, and visualization of data (often at a large scale) using ethical, computationally supported, and statistically valid methods. |
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4: | Statistics with bigger, messier data |
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5: | The science of data gathering, exploration, and manipulation from unstructured or unconventional data sources. |
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6: | big data, integration of statistics and computer scientist, computation, less inferential more prediction focused, grabbing data from multiple sources, data manipulation and cleaning |
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7: | Wrangling real (and really messy) data from any field to address questions about the world.
Data science is a subset of statistics? |
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8: | Data science is an interdisciplinary science that includes statistics, computer science, communication skills, and domain knowledge. |
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9: | combining tools from statistics and computer science to manage and analyze complex data, with greater emphasis on upstream (i.e., before analysis) data processing |
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11: | Application of computational and inferential thinking to a discipline-specific problem. Includes areas outside of statistics such as data management/storage. |
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12: | Integration of statistics, computation, and data management |
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13: | Emerging field involving data management, computation, statistical models, visualization, interpretation, domain knowledge, communication, and decision-focused. |
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