Patterns in Chaos: How Data Visualisation Helps To See the Invisible (mrmcd25) episode artwork

EPISODE · Sep 13, 2025 · 54 MIN

Patterns in Chaos: How Data Visualisation Helps To See the Invisible (mrmcd25)

from Chaos Computer Club - recent audio-only feed · host yote

Full transparency in the sense of "open data" on its own is certainly necessary, but not sufficient, for informed and evidence-based decisions. In addition to data being available, we also require their analysis to be carried out honestly, impartially, and following good statistical practices. An important part of good statistical practice is the (exploratory) visualisation of raw data to generate, and ultimately confirm or reject, new hypotheses. This talk explores how clever data visualisation techniques can uncover complex patterns and reveal hidden connections. Through practical examples, we will illuminate the intricate interplay between data, perception, and insight. https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://talks.mrmcd.net/2025/talk/RLCVEX/

Full transparency in the sense of "open data" on its own is certainly necessary, but not sufficient, for informed and evidence-based decisions. In addition to data being available, we also require their analysis to be carried out honestly, impartially, and following good statistical practices. An important part of good statistical practice is the (exploratory) visualisation of raw data to generate, and ultimately confirm or reject, new hypotheses. This talk explores how clever data visualisation techniques can uncover complex patterns and reveal hidden connections. Through practical examples, we will illuminate the intricate interplay between data, perception, and insight. https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://talks.mrmcd.net/2025/talk/RLCVEX/

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Patterns in Chaos: How Data Visualisation Helps To See the Invisible (mrmcd25)

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This episode was published on September 13, 2025.

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Full transparency in the sense of "open data" on its own is certainly necessary, but not sufficient, for informed and evidence-based decisions. In addition to data being available, we also require their analysis to be carried out honestly,...

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