I skimmed through your other thread to see exactly how receptive you are to feedback.
You continually assume, despite zero formal training, that everyone else is wrong or lacking in understanding.
You did it to me, suggesting I was the one needing more education when you linked that VS stuff, which I was already familiar with from when it was argued. My only interest would have been to know what was discussed between iskar and them in DMs.
I did not comment on your link because it actually undermines the entirety of your work if you understand it on more than a surface level.
This is you being factually incorrect. The sample is collected in a way where the number of 0s is equal to the number of ones. Both the sample and the population mean are 0.5, although in the case of the population mean it’s based on theory, with the sample mean it’s based on methodology.
Either admit this or explain how I’m wrong. But do NOT say “oh, I paid for a piece of paper that says I’m smarter than you.”
The federal government paid for them, actually, unless you count my payment in blood in suffering as a trade in kind, which they do.
No, is you not letting yourself see other sides of the issue due to a lack of fundamental knowledge.
The part you are talking about is not the part I am talking about, but yes, the mean is neutral in binary data. This underlying data is not what you are comparing.
But again, rather then genuinely seeking information, you are assuming everyone else is wrong and attacking, so I have no interest in helping you get better at anything.
At the end of the day, you’re working with data that is insufficient to produce high standard results, and as such you will never satisfy people with a professional interest in statistical analysis. Should you have to? Because imo this is the most useful feedback
None of this means your analyses have nothing of interest or value.
I can’t remember that one, I’ll have to watch it again. You have moved to the “esteemed” category for the SouthPark reference. Please accept my apologies.