Abstract
Data analysis is essential for understanding the phenomena observed in the actual environment. Data analysis forms a workflow consisting of data acquisition, collection, visualization and quantification, and interpretation. The purpose of data analysis is to find insights into phenomena that we have attended to and make decision-makers change their behavior. Data utilization should form an improvement cycle with Check, Action, Plan, and Do (CAPD). This chapter shows a fundamental definition of data (four types of data formats, such as time series, network, spatial, and linguistic data). Several methodological frameworks for analyzing data and how to use the results obtained from data analysis are discussed.
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Sato, AH. (2019). Practical Methods for Data Analysis. In: Sato, AH. (eds) Applications of Data-Centric Science to Social Design. Agent-Based Social Systems, vol 14. Springer, Singapore. https://doi.org/10.1007/978-981-10-7194-2_2
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DOI: https://doi.org/10.1007/978-981-10-7194-2_2
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