This website is supposed to be about using statistically significant data as the basis for drawing reasonable conclusions.
If any test that people can run is truly flawed because of the equipment, no matter how many times you measure it, then you aren’t using the right equipment. And while many people can be forgiven for not knowing the equipment’s shortcomings, due to ignorance, if you know the equipment is insufficient and keep using it anyway, then you are part of the problem.
In my worldview, it’s always best to assume ignorance, not malice. But if someone knows the testing methodology is flawed and publishes the results anyway, then I lean back towards malice.
For instance, if I decided to test a hypothesis that Hornady bullets aren’t consistently the same length and this was how I was going to prove it, you would rightly suspect me of being ignorant, stupid, or dishonest.
But if I said, I am going to use this tool to do it, most people would accept that I was at least trying.
A handful would suggest that I don’t have the expertise in using a dial caliper to be the right person to conduct the test. And a few more would suggest that this particular dial caliper is not good enough or hasn’t been calibrated properly. And a bunch of people would point out that grabbing five random bullets out of one box is too small a sample size to show anything.
And if I persisted in doing the test without proper experience, with the wrong tool, with too small a sample size, then my conclusions would be essentially worthless. And if I concluded that Hornady bullets are the finest on the market and everyone should buy them, you might suspect I was dishonest, not just ignorant or stupid.
So, is the equipment commonly available the equivalent of a kid’s measuring stick? Or a decent dial caliper? Or something more?
Are the people operating it lawyers trying to make an argument? Or salesmen trying to make a sale? Or are they skilled technicians who know what they are doing?
I simply refuse to believe that the equipment is so bad that a large enough data sample won’t provide useful information. If it is, then publish something that says that and show the data that supports that conclusion. All I have read and heard on RokSlide and the podcast is basically, “our ears and the meters don’t agree, so the meters are wrong.” Or, “the results vary so widely from one day to the next that it’s hard to draw conclusions.”
Any honest person could run a test that takes into account the environmental conditions by making them part of the average and recording them in the report. It’s just a lot of work and probably costs a lot of time and money.