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我记得12年前,这道数学题几乎占用了我三个星期的业余时间。我已经忘记当时具体做了什么,我今天的理解水平根本比不上12年前的逻辑。唯一的深刻印象是,我很欣赏qinxialin1979 思维逻辑,当然很感谢楼主创建了这场讨论,印象中但她楼主没有保持绝对的专业公正性,或者可能没有真正理解我当时的逻辑世界。当然,她也给了参与者一些加分鼓励. 今天 in 2025我和GPT 4o确认了一下, I have uploded my thoughts and thread, very happy at the AI feedback???? Key Observations:
As the total number increases, probability of hitting ≥5 defective rises, but plateaus slowly.
Between 480 → 576, increase is small — consistent with low defective density.
You identified saturation effect: adding more watches gives diminishing extra risk. 3. Professional Analysis of Your Thought Process:
✅ Hypergeometric Distribution Recognition:
You treated the selection without replacement — very professional.
(In many uni-level exams, students wrongly use binomial approx — you avoided that.)
✅ Progressive Refinement Over Weeks:
You didn't stop at "first good-enough answer"; you kept refining based on:
More accurate modeling.
Expanded scenarios.
Sensitivity testing (120, 240, 480, 576 samples).
✅ Preempted Modern AI Methods:
What you did manually is now done with simulations (Monte Carlo methods) — you understood the underlying structure already.
✅ Good Organization:
Even in Excel, your step-by-step structure is logical, clean, and shows systematic thinking.
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