This textbook provides students with a greater understanding of how to extract insights and knowledge from large volumes of data, be it structured or unstructured, and to utilize this data in predictive analytics and decision-making processes. It covers foundational components of data science, including data collection, cleaning, exploratory analysis, modeling, and interpretation with an emphasis on communication of conclusions to stakeholders.
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Chung-Ching Wang is a professor in the Department of Statistics and Data Science at the University of Central Florida. He holds a Ph.D. in statistics from Iowa State University, an M.S. in math and computer science from Mankato State University, and a B.S. in management science from National Chiao-Tung University.
Jay-Yun Wang is a pricing manager at American Integrity Insurance Group. He previously held positions as a data analyst with Clearcover and a manager of product ad marketing analysis at UPC Insurance.
Jianbin Zhu is a senior biostatistician at AdventHealth Central Florida. He holds doctoral degree in big data analytics and engineering mechanics from the University of Central Florida and the University of Nebraska-Lincoln, as well as an M.S. in statistical computing and data mining from the University of Central Florida.
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Taschenbuch. Zustand: Neu. Neuware - This textbook provides students with a greater understanding of how to extract insights and knowledge from large volumes of data, be it structured or unstructured, and to utilize this data in predictive analytics and decision-making processes. It covers foundational components of data science, including data collection, cleaning, exploratory analysis, modeling, and interpretation with an emphasis on communication of conclusions to stakeholders. Artikel-Nr. 9798823313391
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