Editing Talk:2560: Confounding Variables
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Her argument is exceedingly weak. If you simply want to note a correlation, there's no need to control for any confounding variables. If, on the other hand, you want to prove a causative relationship, there is simply no way to do that by controlling for any set of potentially confounding variables - but contrary to her assertion, this doesn't mean that stats are a farce and the truth is unknowable, it just means that a causative relationship can only be established experimentally. To establish a causative relationship, you don't need to control for any confounding variables, you just randomize. Example in a clinical trial, patients are randomly assigned to the treatment group or the placebo group. There's no need to control for anything because random chance would distribute patients with any potential confounding variable throughout both groups. You use appropriate statistical significance tests to make sure that this effect of random chance is sufficient to be reasonably sure of the results, and you have the truth. The argument this individual is making is based on misunderstandings of statistical principles prevalent in popular culture. | Her argument is exceedingly weak. If you simply want to note a correlation, there's no need to control for any confounding variables. If, on the other hand, you want to prove a causative relationship, there is simply no way to do that by controlling for any set of potentially confounding variables - but contrary to her assertion, this doesn't mean that stats are a farce and the truth is unknowable, it just means that a causative relationship can only be established experimentally. To establish a causative relationship, you don't need to control for any confounding variables, you just randomize. Example in a clinical trial, patients are randomly assigned to the treatment group or the placebo group. There's no need to control for anything because random chance would distribute patients with any potential confounding variable throughout both groups. You use appropriate statistical significance tests to make sure that this effect of random chance is sufficient to be reasonably sure of the results, and you have the truth. The argument this individual is making is based on misunderstandings of statistical principles prevalent in popular culture. | ||
[[Special:Contributions/172.68.174.150|172.68.174.150]] 18:46, 30 August 2023 (UTC) | [[Special:Contributions/172.68.174.150|172.68.174.150]] 18:46, 30 August 2023 (UTC) | ||
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