I don't think this is off topic at all. I think is is explicitly on topic, at least the the underlying one. Not just statistics are hard, but it's hard to measure things and even harder to determine causality. Which is often the underlying goal of statistics and data science. To find out why things happen. Measurements are incredibly difficult and people often think they are simple. The problem is that whatever you're measuring is actually always a proxy and has uncertainty. Often uncertainty you won't know about if you don't have a good understanding of what the metric means. You'll always reap the rewards when putting in the hard work to do this, but unfortunately if you don't it can take time before the seams start to crack. I think this asymmetry is often why people get sloppy.