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#119 Data-Driven Thinking for the Everyday Life

DataFramed

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Self-Tracking for Personal Insights

This chapter focuses on the methodologies of data mining versus traditional experimental statistics in personal scientific practices, emphasizing self-tracking as a valuable tool for mental health reflection. It discusses the importance of crafting purposeful questions for effective data collection, enhancing personal understanding of one's emotional patterns and health behaviors. Through various case studies, the chapter illustrates how simple metrics can lead to significant self-discoveries and behavioral changes.

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