第 25195 題：估計量均方誤差

原題與已知條件

scalar theta下完整finite sampling law的exact expected squared error。操作=mse-zero-iff-almost-sure；資料={"theta":7,"support":[7,12],"probabilities":[1,0]}。請依 exact_ordered_tuple_declared_by_interface 欄序回答。

• G001 — scalar theta下完整finite sampling law的exact expected squared error。操作=mse-zero-iff-almost-sure；資料={"theta":7,"support":[7,12],"probabilities":[1,0]}。請依 exact_ordered_tuple_declared_by_interface 欄序回答。

定義與適用範圍

沿用原題明示的論域、假設與來源 MKO 定義。本題已完成第二對話數理與中英語義覆核，並由原始參數逐題獨立重算模型、答案與每個算術步驟；原題仍為 candidate。

• mko-estimator-mean-squared-error

逐步推導

source roles = [mse-zero-iff-almost-sure]

derived = [[theta, weighted_error_rows, MSE, zero_MSE, almost_surely_equal_theta, equivalence_holds, certificate]]

MSE ORIGINAL single theta ORIGINAL probability cumulative0 := sum(0, 1)

MSE ORIGINAL single theta ORIGINAL probability cumulative0 = 1

MSE ORIGINAL single theta ORIGINAL probability cumulative1 := sum(1, 0)

MSE ORIGINAL single theta ORIGINAL probability cumulative1 = 1

source roles = [MSE ORIGINAL single theta, 7, [7, 12], [1, 0]]

derived = [[[7, 1], [12, 0]], 1]

MSE ORIGINAL single theta exact mean product0 := mul(7, 1)

MSE ORIGINAL single theta exact mean product0 = 7

MSE ORIGINAL single theta exact mean cumulative0 := sum(0, 7)

MSE ORIGINAL single theta exact mean cumulative0 = 7

MSE ORIGINAL single theta exact mean product1 := mul(12, 0)

MSE ORIGINAL single theta exact mean product1 = 0

MSE ORIGINAL single theta exact mean cumulative1 := sum(7, 0)

MSE ORIGINAL single theta exact mean cumulative1 = 7

MSE ORIGINAL single theta error row0 := sub(7, 7)

MSE ORIGINAL single theta error row0 = 0

MSE ORIGINAL single theta squared error row0 := mul(0, 0)

MSE ORIGINAL single theta squared error row0 = 0

MSE ORIGINAL single theta weighted error row0 := mul(1, 0)

MSE ORIGINAL single theta weighted error row0 = 0

MSE ORIGINAL single theta MSE cumulative0 := sum(0, 0)

MSE ORIGINAL single theta MSE cumulative0 = 0

MSE ORIGINAL single theta error row1 := sub(12, 7)

MSE ORIGINAL single theta error row1 = 5

MSE ORIGINAL single theta squared error row1 := mul(5, 5)

MSE ORIGINAL single theta squared error row1 = 25

MSE ORIGINAL single theta weighted error row1 := mul(0, 25)

MSE ORIGINAL single theta weighted error row1 = 0

MSE ORIGINAL single theta MSE cumulative1 := sum(0, 0)

MSE ORIGINAL single theta MSE cumulative1 = 0

source roles = [MSE ORIGINAL single theta, 7, [[7, 1, 0, 0], [12, 0, 25, 0]]]

derived = [7, 0, 是, 是, 是]

逐步反向核對

• S017 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S016 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta MSE cumulative1，不以小數近似替代。
• S015 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta weighted error row1，不以小數近似替代。
• S014 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta squared error row1，不以小數近似替代。
• S013 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta error row1，不以小數近似替代。
• S012 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta MSE cumulative0，不以小數近似替代。
• S011 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta weighted error row0，不以小數近似替代。
• S010 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta squared error row0，不以小數近似替代。
• S009 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta error row0，不以小數近似替代。
• S008 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta exact mean cumulative1，不以小數近似替代。
• S007 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta exact mean product1，不以小數近似替代。
• S006 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta exact mean cumulative0，不以小數近似替代。
• S005 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta exact mean product0，不以小數近似替代。
• S004 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。
• S003 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta ORIGINAL probability cumulative1，不以小數近似替代。
• S002 · premise_and_result_audit — 以精確有理數重算 MSE ORIGINAL single theta ORIGINAL probability cumulative0，不以小數近似替代。
• S001 · premise_and_result_audit — 回到原始資料與本步條件核對，不把單向推論誤稱等價。

結論

(7, [[7, 1, 0, 0], [12, 0, 25, 0]], 0, 是, 是, 是, nonnegative_squared_terms_make_zero_MSE_equivalent_to_T_equals_theta_almost_surely)

依上列完整代值及條件核對得到原題答案；原題編號、格式與狀態保持不變。

本題覆核與來源綁定

覆核日期：2026-10-26

原題、答案、步驟表達式、數值 AST 與既有歷史保持原樣；原來的候選狀態屬於來源歷史，不覆寫為形式化證明。