Videos: Bad data
This resource page has 2 videos:
- Why what I see is not quite the way it really is (3 min)
- Bad data (7 min)
Why what I see is not quite the way it really is
This video sets the scene for “Why what I see is never the way it really is.” It introduces the distinction between facts and artefacts, and the first law of data analysis, “Garbage in, Garbage out”.
(See also the Review Questions following the movie)
[Illustrated transcript (pdf)]
After you’ve watched this video, you should be able to answer these questions:
- What is the first law of data analysis?
- Can sophisticated data analysis turn bad data into reliable conclusions?
- In terms of the patterns we see in data, what is the difference between facts and artefacts?
Bad data
What makes data go bad? We’ll talk about sources of systematic bias through inadequacies in the measurement, classification and selection processes that produced the dataset, and the need to distinguish between facts and artefacts.
(See also the Review Questions following the movie)
[Illustrated transcript (pdf)]
After you’ve watched this video, you should be able to answer these questions:
- What are artefacts?
- What are the two main ways that systematic biases get into data?
- Why can missing values cause biases?
- What is the best way investigators can protect themselves against bad data?
