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Openai/691718ed-7ba4-8006-96d5-a66e0d9678fe
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==== 這個例子就是「性別統計」遇上「虛無假設」的典型應用： ==== * 性別統計 → 我們觀察出生嬰兒的性別比例。 * 虛無假設 → 假設男女出生機率相等。 * 統計檢定 → 用數據來判斷觀察到的差異是否顯著。 * 政策或研究應用 → 如果差異顯著，可能引發對醫療、遺傳或環境因素的研究。 要不要我幫你畫一個「從資料 → 虛無假設 → 檢定 → 結論」的流程圖，用男嬰/女嬰出生率的例子把整個思路直觀化？
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