Synopsis
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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About the Authors
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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Paperback. Condition: new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798823313391
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Taschenbuch. Condition: 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. Seller Inventory # 9798823313391
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