The NHTSA were using different data, since they had the non-redacted version. The author uses the redacted version, doesn’t attempt to find an explanation for

The NHTSA were using different data, since they had the non-redacted version. The author uses the redacted version, doesn’t attempt to find an explanation for anomalies, proceeds to analyse data based on faulty initial assumptions, and compounds this by using a cherry picked example where the poorly understood numbers best match their faulty assumptions. When there is no explanation for “airbags deployed before 0km on odometer” there is no point analysing the rest of the data. It’s all bogus, especially the stuff that looks like it makes sense. The fundamental fault of the author’s analysis is trusting data that is proven untrustable. In the same set of data which has some cars deploying airbags before ever being driven, the author assumes that the data which matches their model of validity is magically more accurate and thus worthy of study. The author continues to trust this data because it supports their biases, even while pointing out the errors in the rest of the data. How is this not cherry picking? The entire study is bogus because it starts with bogus data and attempts to make claims about reality based on a subset of bogus data that can be misinterpreted as less bogus. It’s like picking the few pages of manuscript from the infinite monkeys room which have meaningful phrases on them and claiming that obviously monkeys are really good writers.