Data science
Anonymization
Data anonymization is a type of process to remove sensitive information to protect the identity of individuals in datasets.
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Data glossaryCorrelation does not imply causation
Correlation does not imply causation
Data scienceStatistics
An easy mistake to make (a 'logical fallacy') is to draw the conclusion that, because two variables are correlated, one causes the other.
An easy mistake to make (a "logical fallacy") is to draw the conclusion that, just because two things seem related, for example following the same pattern over time, they have the same cause. But, correlation does not imply causation. To really understand cause and effect, a much more detailed investigation using statistical methods is often required.
In practice
For example, there is a correlation between the number of fire fighters sent to a fire and the amount of damage done. If you just looked at a chart, the correlation might suggest that the fire fighters cause the damage.
But in this example, the causing factor is instead the "size of the fire", which correlates with both the number of fire fighters sent and the amount of damage done.
Related terms
Statistics
Confounding Variable
A confounding variable is an outside influence that changes the effect of the dependent and independent variable, potentially leading to false conclusions.
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Data science
Dataset
A dataset is a collection of related tables of data that may be accessed individually or in combination for analysis or reporting.
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