Comment by IanCal
8 hours ago
The other explanation is that often these are just mistakes that occur with a team of experts in their field but not data management, without a budget for building a more robust system, manually doing a lot of things with data. It's so easy to copy and paste something into the wrong place, to sort by a field and get things out of order, all kinds of issues like that.
On the other hand, any time a hypothesis appears significant, the first reaction should be to verify that all the data going into the calculation is correct, rather than just assume it is. In my day-to-day industry experience, significant results come far more often from incorrect data than an actual discovery.