Missing Data Leads to the Wrong Conclusions

In my previous post, Challenging the Evidence in Data Science, I encourage data science teams to be skeptical of any claims or evidence that supports those claims, and I provide several techniques for challenging claims and evidence.

However,...

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Challenging the Evidence in Data Science

Data drives the data science team's exploration and discovery, so the team must be on the constant lookout for bad data, which can lead the team astray or result in erroneous conclusions. In this post, I present several ways to challenge the data...

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Five Approaches to Statistical Analysis

Data science teams capture, store, and analyze data to extract valuable information and insight. In recent posts, I focused on capturing and storing three types of data — structured, semi-structured, and unstructured — and I encouraged...

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