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@aodaimyan.vn: #damlua #vaylua #fyp #viralvideos #aodaimyan
aodaimyan.vn
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Saturday 25 July 2026 13:36:49 GMT
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Yếnn Yếnn :
Ib
2026-07-27 02:27:41
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JuCheng :
🥰🥰🥰
2026-07-26 08:51:19
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#az🥺 #❤️ #حبي #حبني #to
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this reminds me of a fic i once read🫠 i DONT play about ateez x ethel #yunho #ateez #ethelcain #targetaudience
Best way 😏👍🏻
Every time you assume something about a person because of a group they belong to, you're making a specific statistical error. Three books explain why. Start with the core mistake. Average a thousand people's learning curves and you get a smooth, gentle slope — even though not one of them learned smoothly. They each learned in sudden jumps and frustrating plateaus. That's from Farrell and Lewandowsky's *Computational Modeling of Cognition and Behavior*, and it's a cousin of the ecological fallacy. Remember the phrase: the average is nobody. So whenever you hear a group-level statistic — how people learn, heal, eat, behave — resist applying it directly to the person in front of you, or to yourself. The second book sharpens it into an ethical warning: Collins and Lanza's *Latent Class and Latent Transition Analysis*. It teaches you to sort people into hidden statistical categories — useful for prediction, but completely separate from any claim about a person's worth, rights, or fixed destiny. A statistical bucket is a prediction tool, never a verdict. And the last book pulls the rug out, in the best way. Shlomo Sternberg's *Dynamical Systems* shows human behavior has no master equation, no tidy one-line explanation. So when someone acts in a way you don't understand, resist the easy story — "he's just lazy," "that's just human nature." Real behavior emerges from thousands of interacting forces no model fully captures. Flattening a person into a single model isn't just bad statistics. It does them a real disservice. Follow @thinkitthrough411 for more! #DataScience #Statistics #Psychology #TikTokContest #BookTok
#beautifulstichingdesigns#foryou#stiching#
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