Скачать или смотреть I love statistics; nerd out with me for a minute- let's briefly discuss validity.

We don't have to go all the way into the statistics rabbit hole but I want you to see how easily it is to alter data, which in turn makes it invalid. Not only is it the biggest fear of all researchers, it is the biggest no no as a researcher. Altering numbers can literally end your career. Yet, for some reason the narrative that is being painted does not have a control group, nor are we seeing adequate data from unbiased resources. There is no way to accurately determine sampling validity. Basically the data is skewed because of research bias. Why? All part of the plan....
But let's face it, if you do a research study on a 100 terminal people with comorbidity, but have no control group, of course the effector impacted 100% of your people. Unfortunately, correlation is not causation . Therefore, just because you can correlate somebody with having covid when they died does not mean that it is what they died from. It just makes sense that way. Likewise, if you have no alternative or null hypothesis then you're still already proving your bias, which in turn always results in skewed data. Because basically you're demonstrating that you are creating a narrative by looking for specific details to incorporate into your data. It is a study that becomes inconclusive. Research should not be about proving something, rather, discovering. The data should speak for itself, but it should be inclusive of all the data to see the overall bigger picture.