Am I the only one who's more shocked by the LLMs affirming "The distributions appear roughly normal for both genders, as shown in the visualization", "Both distributions appear approximately normal, though with some right skew" and such than by any gorilla issue?
From short thinking or from looking at the graphs I would believe "roughly normal" sounds like wishful thinking to stay in the reassuring bounds of normal distributions. And I believe things would get dangerous once you would start using these assumptions for tests and affirmations.
My short thinking: distributions don't look close to normal on the graphs. Values are probably bounded on one side and almost unbounded on the other (can't go below 0 steps, can go into very high number of steps on 1 day). There are days / people with close to 0 steps and others that might distribute in a sort of normal around a value maybe. Weight and height might be normally distributed in a population but they're correlated and BMI is one divided by the square of the other. I can't compute the resulting distribution but I would doubt that would make for a distribution close to normal.
Ok the LLMs were told to assume both traits were distributed normally, but affirming they look mostly normal is scary to me.
Am I too picky and in real analyses assuming such distributions are "mostly normal" is fine for all practical purposes?
Honestly, this was the meta-gorilla in the data for me! I was so busy focusing on the LLM’s EDA that I didn’t really interrogate some of the other data analysis practices.
In general, I’ve steered clear of current LLMs for data analysis/description because they seem so highly influenced by choice of prompt and wording. They tend to simply affirm any language I use to describe the data initially.
To be fair, I’ve attended conferences and lab meetings where humans will refer to a any vaguely concave curved distribution as “mostly normal” :P
Wondering if Notion might not put you out of business. I have the impression they make it super easy to publish a "simple" page (could have a database) and edit it. Has seen a friend us Notion for that but haven't tried myself.
This is so good. I've just watched his 8 videos explaining from transistors to logic and memory. Wonder why he unfortunately stopped at SS8 : Time and Memory now...
I don't see anything about temperature regulation, wouldn't that be a big energy consuming part? Especially if I picture a container out under the roasting sun or in biting cold.
Same feeling, the fact that one has to assume people will not take 5s to read and understand a message has nothing to do with the project being open-source & free or not.
I feel that it must be even more annoying when you're offering free great work to these people. But I believe it to be a fact about all users (I include myself, though I'm trying to work on it).
From short thinking or from looking at the graphs I would believe "roughly normal" sounds like wishful thinking to stay in the reassuring bounds of normal distributions. And I believe things would get dangerous once you would start using these assumptions for tests and affirmations.
My short thinking: distributions don't look close to normal on the graphs. Values are probably bounded on one side and almost unbounded on the other (can't go below 0 steps, can go into very high number of steps on 1 day). There are days / people with close to 0 steps and others that might distribute in a sort of normal around a value maybe. Weight and height might be normally distributed in a population but they're correlated and BMI is one divided by the square of the other. I can't compute the resulting distribution but I would doubt that would make for a distribution close to normal.
Ok the LLMs were told to assume both traits were distributed normally, but affirming they look mostly normal is scary to me.
Am I too picky and in real analyses assuming such distributions are "mostly normal" is fine for all practical purposes?
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