Data Science jargon buster – for Data Scientists

Data Scientists need to communicate without jargon so customers understand, believe and care about their recommendations. Here is a Data Science jargon buster to help with communicating data science project results.

Data Science is a technical field that applies scientific rigour to the understanding of business data and the associated processes and products. Like traditional science, it can be full of jargon that leads to unclear business messages and a failure of findings to be understood and acted upon. Having reviewed countless Data Science reports and presentations that are not ready for business readers, I thought it would be useful to provide a list of business terms to replace Data Science jargon.

Data Science Jargon Buster

TermData Science JargonBusiness term
1Factor / independent variableinputs
2Dependent variablemetric / KPI/ Outcome
3Monotonically increasingalways increasing
4ClusteringGrouping
5ClassificationLabelling
6RegressionPrediction
7CorrelationRelation, association
8Null HypothesisStatus quo
9Type 1 errorFalse positive / wrong prediction
10Type 2 error Failed to detect the effect
11Sensitivity / RecallCompleteness
12harmonic mean, geometric meanaverage
13Trivialstraight forward
Data Science jargon buster

Eradicating Data Science jargon from your team

Do you have some jargon you would like to eradicate from your team? Get in touch! Let’s build this list together.

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