Difference between revisions of "Power of data"
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=The notion of counter-factuals= | =The notion of counter-factuals= | ||
Data content may not be correct, but noise and lies included, reveal certain qualities and quantities of the realistic context of data collection. For more explainations on counter-factuals, see Judea | Data content may not be correct, but noise and lies included, reveal certain qualities and quantities of the realistic context of data collection. For more explainations on counter-factuals, see [[Judea Pearl]]'s work on causation<ref>{{:Book/Causality:models, reasoning, and inference}}</ref>. | ||
=References= | =References= | ||
<references/> | <references/> | ||
=Related Pages= | |||
[[Category:Data]] | |||
[[Category:Logic]] | |||
[[Category:Causation]] | |||
[[Category:Counter-factual]] | |||
[[Category:Truth]] | |||
Latest revision as of 01:25, 19 February 2022
The power of data comes from its embedded information content that has the potential to reveal truth. Even a set of badly encoded data, could reveal information about its source in ways that are not always intuitive from shallow observations.
The notion of counter-factuals
Data content may not be correct, but noise and lies included, reveal certain qualities and quantities of the realistic context of data collection. For more explainations on counter-factuals, see Judea Pearl's work on causation[1].
References
- ↑ Pearl, Judea (2000). Causality:models, reasoning, and inference. local page: Cambridge University Press. ISBN 978-0-521-77362-1.