{"id":3358,"date":"2025-08-24T00:05:50","date_gmt":"2025-08-23T16:05:50","guid":{"rendered":"https:\/\/yowlab.idv.tw\/wordpress\/?p=3358"},"modified":"2025-08-24T00:41:01","modified_gmt":"2025-08-23T16:41:01","slug":"%e3%80%90%e7%ad%86%e8%a8%98%e3%80%91%e6%90%9e%e7%a0%b8%e4%bd%a0%e6%b1%ba%e7%ad%96%e7%9a%84-20-%e7%a8%ae%e8%aa%8d%e7%9f%a5%e5%81%8f%e8%aa%a4","status":"publish","type":"post","link":"https:\/\/yowlab.idv.tw\/wordpress\/?p=3358","title":{"rendered":"\u3010\u7b46\u8a18\u3011\u641e\u7838\u4f60\u6c7a\u7b56\u7684 20 \u7a2e\u8a8d\u77e5\u504f\u8aa4"},"content":{"rendered":"

\u53bb\u5e74\u6216\u524d\u5e74\u66fe\u7d93\u770b\u904e\u7684\u6587\u7ae0\uff0c\u4f86\u4e0d\u53ca\u505a\u7b46\u8a18\uff0c\u4eca\u5929\u5f37\u8feb\u81ea\u5df1\u628a\u4ed6\u5011\u8a18\u4e0b\u4f86\u3002<\/p>\n\n

\u3010\u641e\u7838\u4f60\u6c7a\u7b56\u7684 20 \u7a2e\u8a8d\u77e5\u504f\u8aa4 \u3011<\/strong> \/ \u674e\u8015\u9298<\/p>\n

\u5927\u7d04\u5169\u5468\u524d\u7ffb\u8b6f\u904e\u8cc7\u6599\u79d1\u5b78\u768415\u500b\u5e38\u898b\u8b2c\u8aa4\uff0c\u9019\u5e7e\u5929\u525b\u597d\u53c8\u770b\u5230\u8ac7\u8a8d\u77e5\u504f\u8aa4(Cognitive bias)\u7684\u6587\u7ae0\uff0c\u8a8d\u77e5\u504f\u8aa4\u5e73\u5e38\u5728\u6211\u5011\u601d\u8003\u6642\u5c31\u5e38\u5e38\u6703\u51fa\u73fe\uff0c\u4e0d\u904e\u500b\u4eba\u8a8d\u70ba\u5927\u8166\u7684\u6f14\u5316\u7d50\u679c\u81ea\u7136\u6703\u671d\u8457\u7bc0\u7701\u80fd\u91cf\u7684\u65b9\u5411\u8d70\uff0c\u9019\u4e5f\u5c0e\u81f4\u4e86\u9019\u4e9b\u8a8d\u77e5\u504f\u8aa4\u7684\u51fa\u73fe\u5176\u5be6\u662f\u5f88\u6b63\u5e38\u7684\u73fe\u8c61\u3002<\/p>\n

\u4f46\u6211\u89ba\u5f97\u5f88\u591a\u6642\u5019\u8981\u7d93\u6b77\/\u88ab\u96fb\u904e\u518d\u56de\u982d\u770b\u624d\u6703\u6709\u5370\u8c61\uff0c\u6240\u4ee5\u5c31\u5148\u59d1\u4e14\u8a18\u8457\uff0c\u4e4b\u5f8c\u6bcf\u6bb5\u65e5\u5b50\u5c31\u56de\u4f86\u770b\u4e00\u4e0b\u3002<\/p>\n

\u4e0b\u6587\u4e2d\u7684\u82f1\u6587\u540d\u8a5e\u7684\u4e2d\u6587\u7ffb\u8b6f\u7d55\u5927\u90e8\u5206\u53c3\u7167\u7dad\u57fa\u767e\u79d1\uff0c\u5982\u6709\u8aa4\u6216\u662f\u66f4\u597d\u7684\u7ffb\u8b6f\u4e5f\u9ebb\u7169\u4f86\u8a0a\u544a\u77e5\u3002<\/p>\n

    \n
  1. \n

    \u9328\u5b9a\u6548\u61c9 (Anchoring bias)<\/strong>
    \n\u6211\u5011\u5728\u8861\u91cf\u50f9\u503c\u6703\u53d7\u4e0a\u4e00\u500b\u63a5\u6536\u5230\u7684\u8cc7\u8a0a\u6240\u5f71\u97ff\uff0c\u4e26\u4ee5\u6b64\u505a\u70ba\u6bd4\u8f03\u57fa\u6e96\uff0c\u6bd4\u65b9\u8aaa\u53f0GG\u5f9e 300 \u4e00\u8def\u6f32\u5230 500 \u4e00\u822c\u4eba\u90fd\u6703\u89ba\u5f97 500 \u600e\u9ebc\u9019\u9ebc\u8cb4\uff0c\u4f46\u5982\u679c\u5f9e 600 \u8dcc\u56de 500 \u5c31\u6703\u89ba\u5f97\u6316\u597d\u4fbf\u5b9c\uff0c\u5e73\u5e73\u80a1\u50f9\u90fd\u662f 500 \u4f46\u611f\u53d7\u537b\u622a\u7136\u4e0d\u540c\u3002<\/p>\n<\/li>\n

  2. \n

    \u53ef\u5229\u7528\u6027\u6377\u601d\u6cd5 (Availability heuristic)<\/strong>
    \n\u9762\u5c0d\u554f\u984c\u6642\u6211\u5011\u6703\u50be\u5411\u76f4\u63a5\u7528\u624b\u908a\u7684\u8cc7\u8a0a\u4f86\u89e3\u7b54\uff0c\u6bd4\u65b9\u8aaa\u5982\u679c\u8eab\u908a\u6709\u4eba\u662f\u8001\u83f8\u69cd\u537b\u4ecd\u7136\u6d3b\u523090\u591a\u6b72\uff0c\u90a3\u9ebc\u6211\u5011\u5c31\u6703\u4e0b\u610f\u8b58\u5730\u8a8d\u70ba\u62bd\u83f8\u5c0d\u5065\u5eb7\u662f\u7121\u5bb3\u7684\uff0c\u4e8b\u5be6\u4e0a\u8981\u4e0b\u5b9a\u8ad6\u524d\u61c9\u8a72\u8981\u76e1\u53ef\u80fd\u5730\u5f9e\u7d71\u8a08\u6578\u64da\u8207\u5be6\u9a57\u4e2d\u53d6\u5f97\u3002<\/p>\n<\/li>\n

  3. \n

    \u5f9e\u773e\u6548\u61c9 (Bandwagon effect)<\/strong>
    \n\u5728\u7fa4\u9ad4\u4e2d\u6211\u5011\u6703\u50be\u5411\u63a5\u53d7\u3001\u8d0a\u540c\u96c6\u9ad4\u7684\u610f\u898b\uff0c\u800c\u9078\u64c7\u6975\u5c0f\u5316\u500b\u4eba\u7684\u5dee\u7570\uff0c\u50cf\u662f\u539a\u5976\u8336\u3001\u8461\u5f0f\u86cb\u5854\u4e4b\u985e\u7684\u71b1\u6f6e\u4e5f\u662f\u5982\u6b64\uff0c\u5225\u4eba\u505a\u751a\u9ebc\u6211\u4e5f\u60f3\u505a\u751a\u9ebc\u3002<\/p>\n

    \u53e6\u5916\uff0c\u9019\u4e5f\u662f\u70ba\u4ec0\u9ebc\u4eba\u6578\u592a\u591a\u7684\u6703\u8b70\u662f\u6beb\u7121\u751f\u7522\u529b\u7684\u3002<\/p>\n<\/li>\n

  4. \n

    \u504f\u898b\u76f2\u9ede (Blind-spot bias)<\/strong>
    \n\u5c31\u50cf\u5e73\u6642\u7761\u89ba\u6253\u547c\u4e0d\u6703\u5435\u5230\u81ea\u5df1\u4e00\u822c\uff0c\u6211\u5011\u6c92\u6709\u8fa6\u6cd5\u610f\u8b58\u5230\u81ea\u5df1\u7684\u504f\u898b\u3002\u5927\u5bb6\u90fd\u6703\u8a8d\u70ba\u81ea\u5df1\u6700\u4e2d\u7acb\uff0c\u5176\u9918\u8ddf\u6211\u4e0d\u540c\u7684\u90fd\u662f\u504f\u6fc0\u7684\u3002<\/p>\n<\/li>\n

  5. \n

    \u652f\u6301\u9078\u64c7\u504f\u8aa4 (Choice-supportive bias)<\/strong>
    \n\u505a\u4e86\u9078\u64c7\u4ee5\u5f8c\uff0c\u4eba\u5011\u6703\u5168\u7136\u652f\u6301\u4e26\u4e14\u76f8\u4fe1\u81ea\u5df1\u7684\u9078\u64c7\uff0c\u5c31\u662f\u655d\u5e1a\u81ea\u73cd\u7684\u6982\u5ff5\u3002\u4eba\u5011\u5f88\u96e3\u627f\u8a8d\u6216\u9762\u5c0d\u5176\u5be6\u81ea\u5df1\u7576\u521d\u505a\u4e86\u932f\u8aa4\u7684\u9078\u64c7\uff0c\u4e0d\u7ba1\u662f\u5a5a\u59fb\u3001\u5de5\u4f5c\u3001\u653f\u6cbb\u90fd\u662f\u5982\u6b64\uff0c\u4e00\u90e8\u5206\u4e5f\u662f\u6211\u5011\u7684\u9632\u885b\u6a5f\u5236\u4f7f\u7136\uff0c\u4e00\u4f46\u627f\u8a8d\u4e86\u932f\u8aa4\uff0c\u6211\u5011\u53ef\u80fd\u6703\u9677\u65bc\u7121\u6b62\u5883\u7684\u5f8c\u6094\u4e2d\u7121\u6cd5\u81ea\u62d4\u3002<\/p>\n<\/li>\n

  6. \n

    \u96c6\u7fa4\u932f\u89ba (Clustering illusion)<\/strong>
    \n\u8ddf\u4e4b\u524d\u7ffb\u8b6f\u904e\u7684\u8ced\u5f92\u8b2c\u8aa4 (Gambler\u2019s fallacy)\u6709\u9ede\u985e\u4f3c\uff0c\u4eba\u8166\u6703\u81ea\u52d5\u5728\u904e\u5c0f\u7684\u6a23\u672c\u6216\u6b21\u6578\u4e2d\u627e\u5c0b\u898f\u5247\uff0c\u5373\u4fbf\u662f\u96a8\u6a5f\u4e5f\u662f\u5982\u6b64\uff0c\u5c31\u50cf\u662f\u5927\u6a02\u900f\u525b\u51fa\u4f86\u7684\u6642\u5019\uff0c\u4eba\u5011\u767c\u73fe\u524d\u5e7e\u671f\u7684\u4e2d\u734e\u865f\u78bc\u8f03\u5e38\u51fa\u73fe\u67d0\u4e9b\u7279\u5b9a\u865f\u78bc\uff0c\u65bc\u662f\u5c31\u6703\u8a8d\u70ba\u9019\u4e9b\u865f\u78bc\u5c31\u662f\u6bd4\u8f03\u5bb9\u6613\u51fa\u73fe\u7684\u3002<\/p>\n<\/li>\n

  7. \n

    \u78ba\u8a8d\u504f\u8aa4 (Confirmation bias)<\/strong>
    \n\u53ea\u807d\u7684\u5230\u81ea\u5df1\u60f3\u807d\u7684\u8a71\uff0c\u5728\u4e00\u4e32\u5c0d\u8a71\u4e2d\u4eba\u8166\u6703\u50be\u5411\u63a5\u6536\u90a3\u4e9b\u8207\u81ea\u5df1\u504f\u898b\u76f8\u7b26\u7684\u8cc7\u8a0a\uff0c\u8207\u4e4b\u4e0d\u7b26\u7684\u5c31\u81ea\u52d5\u904e\u6ffe\uff0c\u6240\u4ee5\u504f\u898b\u4e00\u4f46\u5f62\u6210\u5f8c\u5bb9\u6613\u4e0d\u65b7\u5730\u5f37\u5316\uff0c\u9069\u7576\u5730\u5fa9\u8ff0\u5225\u4eba\u7684\u610f\u898b\u6703\u6709\u4e00\u4e9b\u5e6b\u52a9\u3002<\/p>\n<\/li>\n

  8. \n

    \u4fdd\u5b88\u6027\u504f\u5dee (Conservatism bias)<\/strong>
    \n\u7576\u6211\u5011\u5c0d\u67d0\u7a2e\u8ad6\u9ede\u7522\u751f\u504f\u898b\u8207\u50f9\u503c\u89c0\u539a\uff0c\u5c31\u6703\u5f88\u96e3\u63a5\u53d7\u65b0\u7684\u8ad6\u9ede\uff0c\u50cf\u662f\u5e03\u9b6f\u8afe\u652f\u6301\u54e5\u767d\u5c3c\u63d0\u51fa\u7684\u5730\u52d5\u8aaa\u4e4b\u5f8c\uff0c\u88ab\u7576\u6642\u7684\u4e3b\u6d41\u610f\u898b\u8996\u70ba\u7570\u7aef\u800c\u6d3b\u6d3b\u71d2\u6b7b\u3002\u53c8\u6216\u8005\u5be6\u76f8\u5c0d\u8ad6\u525b\u88ab\u63d0\u51fa\u4f86\u7684\u90a3\u5e7e\u5e74\u6240\u7d93\u6b77\u7684\uff0c\u60f3\u8981\u6311\u6230\u773e\u4eba\u7684\u50f9\u503c\u6216\u89c0\u9ede\u5c31\u9700\u8981\u6e96\u5099\u7d93\u904e\u5927\u91cf\u7684\u8ad6\u6230\u3002<\/p>\n<\/li>\n

  9. \n

    \u8cc7\u8a0a\u504f\u8aa4 (Information bias)<\/strong>
    \n\u6211\u5011\u5728\u4e0b\u6c7a\u5b9a\u6642\u901a\u5e38\u6703\u5148\u8490\u96c6\u8cc7\u6599\uff0c\u4f46\u5176\u5be6\u8d8a\u591a\u8cc7\u6599\u4e0d\u4ee3\u8868\u4e0b\u7684\u6c7a\u7b56\u5c31\u6703\u8d8a\u7cbe\u6e96\uff0c\u4e00\u65b9\u9762\u662f\u56e0\u70ba\u7db2\u8def\u4e0a\u7684\u8cc7\u6599\u53c3\u5dee\u4e0d\u9f4a(\u50cf\u6700\u8fd1\u5f88\u7d05\u7684\u809d\u81bd\u6392\u77f3\u6cd5)\uff0c\u53e6\u4e00\u65b9\u9762\u8cc7\u8a0a\u8d8a\u591a\u53cd\u800c\u6703\u8b93\u4eba\u66f4\u96e3\u4e0b\u6c7a\u5b9a\u3002<\/p>\n<\/li>\n

  10. \n

    \u9d15\u9ce5\u6548\u61c9 (Ostrich effect)<\/strong>
    \n\u7d93\u5178\u7684\u9d15\u9ce5\u6548\u61c9\uff0c\u6211\u5011\u4e0d\u9858\u610f\u53bb\u6b63\u8996\u90a3\u4e9b\u4e0d\u60f3\u770b\u5230\u7684\u58de\u6d88\u606f\uff0c\u5c31\u50cf\u662f\u9d15\u9ce5\u628a\u982d\u57cb\u5728\u6c99\u4e2d\u5c31\u770b\u4e0d\u5230\u63a0\u98df\u8005\u4e00\u822c\uff0c\u5716\u4e2d\u8209\u7684\u4f8b\u5b50\u662f\u8ca1\u7d93\u7814\u7a76\u54e1\u5728\u718a\u5e02\u6642\u5efa\u8b70\u5ba2\u6236\u6aa2\u8996\u81ea\u5df1\u8cc7\u7522\u76c8\u8667\u7684\u6b21\u6578\u662f\u6e1b\u5c11\u7684\u3002\u6240\u8b02\u7684\u300c\u4e00\u5f35\u4e0d\u8ce3\uff0c\u5947\u8e5f\u81ea\u4f86\u3002\u300d\u4e5f\u6709\u4e9b\u9019\u7a2e\u610f\u5473\u5728(\u770b\u770b HTC……)\u3002<\/p>\n<\/li>\n

  11. \n

    \u7d50\u679c\u504f\u8aa4 (Outcome bias)<\/strong>
    \n\u7528\u7d50\u679c\u4f86\u8a55\u50f9\u6c7a\u7b56\u7684\u6b63\u78ba\u6027\uff0c\u4eca\u5929\u6211\u8cb7\u522e\u522e\u6a02\u8cfa\u4e86\u5927\u9322\uff0c\u90a3\u9ebc\u5c31\u4e0b\u610f\u8b58\u5730\u8a8d\u70ba\u8ced\u535a\u662f\u597d\u7684\u884c\u70ba\uff0c\u5ffd\u7565\u4e86\u4e00\u6642\u7684\u8f38\u8d0f\u53ef\u80fd\u4e5f\u53ea\u662f\u5076\u7136\u3002<\/p>\n<\/li>\n

  12. \n

    \u904e\u5ea6\u81ea\u4fe1 (Overconfidence)<\/strong>
    \n\u81ea\u6211\u611f\u89ba\u826f\u597d\uff0c\u5c0d\u81ea\u5df1\u7684\u5c08\u696d\u6216\u80fd\u529b\u904e\u5ea6\u6709\u81ea\u4fe1\u5c0e\u81f4\u5931\u8aa4\uff0c\u9019\u9ede\u5728\u80a1\u7968\u4ea4\u6613\u4e2d\u975e\u5e38\u5e38\u898b\uff0c\u5927\u5bb6\u90fd\u8a8d\u70ba\u81ea\u5df1\u80fd\u5920\u6253\u6557\u5927\u76e4\u7d50\u679c\u901a\u5e38\u90fd\u662f\u88ab\u5927\u76e4\u6253\u6557\u3002\u800c\u5b78\u6709\u5c08\u7cbe\u7684\u5c08\u5bb6\u66f4\u5bb9\u6613\u72af\u4e0b\u9019\u500b\u932f\u8aa4\u3002<\/p>\n<\/li>\n

  13. \n

    \u5b89\u6170\u5291\u6548\u61c9 (Placebo effect)<\/strong>
    \n\u53ea\u8981\u4f60\u76f8\u4fe1\uff0c\u5b83\u5c31\u771f\u7684\u6703\u6709\u6548\uff0c\u4e5f\u56e0\u6b64\u5728\u91ab\u5b78\u4e0a\u5be6\u9a57\u4e0a\u6e2c\u8a66\u7642\u6548\u6642\u901a\u5e38\u6703\u5206\u6210\u5be6\u9a57\u7d44\u8207\u5c0d\u7167\u7d44\uff1a\u5be6\u9a57\u7d44\u7d66\u771f\u6b63\u8981\u6e2c\u8a66\u7684\u85e5\uff0c\u53e6\u4e00\u7d44\u5247\u7d66\u4e88\u5b89\u6170\u5291\uff0c\u5c31\u662f\u70ba\u4e86\u6d88\u9664\u5b89\u6170\u5291\u6548\u61c9\u3002<\/p>\n

    \u6709\u4e00\u6d3e\u8aaa\u6cd5\u662f\uff1a\u5438\u5f15\u529b\u6cd5\u5247\u7684\u80cc\u5f8c\u5176\u5be6\u4e5f\u662f\u5b89\u6170\u5291\u6548\u61c9\u3002<\/p>\n<\/li>\n

  14. \n

    \u652f\u6301\u5275\u65b0\u504f\u8aa4 (Pro-Innovation bias)<\/strong>
    \n\u904e\u5ea6\u8a87\u5927\u65b0\u79d1\u6280\u7684\u61c9\u7528\u3001\u5e02\u5834\u3001\u89e3\u6c7a\u554f\u984c\u7684\u80fd\u529b\uff0c\u7406\u60f3\u5f88\u8c50\u6eff\uff0c\u73fe\u5be6\u537b\u5f88\u9aa8\u611f\uff0c\u60f3\u60f3\u5c0f\u6642\u5019\u770b\u7684\u54c6\u5566A\u5922\u5728\u63cf\u8ff021\u4e16\u7d00\u7684\u6642\u5019\u662f\u5982\u4f55\u5929\u99ac\u884c\u7a7a\u7684\uff0c\u4f46\u7576\u6211\u5011\u771f\u6b63\u9032\u523021\u4e16\u7d00\u624d\u767c\u73fe\u9664\u4e86 3C \u8207\u7db2\u8def\u5927\u8209\u9032\u5165\u751f\u6d3b\u5916\uff0c\u5176\u9918\u7684\u4e00\u5207\u6539\u8b8a\u5176\u5be6\u4e0d\u591a\u3002<\/p>\n

    \u500b\u4eba\u7684\u60f3\u6cd5\u662f\u90a3\u4e9b\u8a8d\u70baAI\u80fd\u5920\u76f4\u63a5\u53d6\u4ee3\u91ab\u5e2b\u6216\u5f8b\u5e2b\u5de5\u4f5c\u7684\u4eba\uff0c\u4e5f\u662f\u72af\u4e86\u652f\u6301\u5275\u65b0\u504f\u8aa4\u3002<\/p>\n<\/li>\n

  15. \n

    \u6642\u8fd1\u6548\u61c9 (Recency)<\/strong>
    \n\u5728\u5f62\u5851\u89c0\u9ede\u6642\uff0c\u6211\u5011\u6703\u76f4\u63a5\u50be\u5411\u63a1\u7d0d\u6700\u8fd1\u7684\u8cc7\u8a0a\uff0c\u5c31\u50cf\u662f\u6bcf\u6b21\u80a1\u7968\u767c\u751f\u6f32\u8dcc\u6642\uff0c\u5831\u7ae0\u5a92\u9ad4\u5c31\u6703\u958b\u59cb\u5f9e\u6700\u8fd1\u7684\u65b0\u805e\u6216\u4e8b\u4ef6\u4e2d\u627e\u5c0b\u7406\u7531\u4e00\u822c\u3002<\/p>\n

    \u9019\u8ddf\u6240\u8b02\u7684\u7b2c\u4e00\u5370\u8c61\u662f\u5b8c\u5168\u76f8\u53cd\u7684\uff0c\u5728\u525b\u8a8d\u8b58\u6642\u7684\u7b2c\u4e00\u5370\u8c61\u6700\u70ba\u91cd\u8981\uff0c\u4f46\u7576\u4e45\u672a\u898b\u9762\u6642\uff0c\u6642\u8fd1\u6548\u61c9\u7684\u5f71\u97ff\u5c31\u6703\u958b\u59cb\u986f\u73fe\uff0c\u5c31\u50cf\u662f\u904e\u5e74\u4e45\u672a\u898b\u9762\u7684\u89aa\u621a\u7e3d\u662f\u6703\u958b\u53e3\u5c31\u662f\u300c\u5509\u5537\uff0c\u73fe\u5728\u90fd\u9577\u9019\u9ebc\u5927\u4e86\uff0c\u9084\u8a18\u5f97\u4ee5\u524d\u4f60\u9084\u597d\u5c0f\u8036\uff01\u300d\u3002<\/p>\n<\/li>\n

  16. \n

    \u986f\u8457\u6027\u504f\u8aa4 (Salience)<\/strong>
    \n\u53ea\u6ce8\u610f\u5230\u6bd4\u8f03\u6709\u7279\u8272\u7684\u8cc7\u8a0a\uff0c\u800c\u5ffd\u7565\u4e86\u6574\u9ad4\u3002\u5e38\u807d\u5230\u7684\u7b11\u8a71\uff1a
    \n\u300c\u6211\u53ef\u4e0d\u53ef\u4ee5\u8ddf\u4f60\u8b1b\u96fb\u8a71\u6642\u6253\u904a\u6232\uff1f\u300d
    \n\u300c\u6211\u53ef\u4e0d\u53ef\u4ee5\u5728\u6253\u904a\u6232\u6642\u8ddf\u4f60\u8b1b\u96fb\u8a71\uff1f\u300d
    \n\u9019\u5169\u8005\u5176\u5be6\u662f\u4e00\u6a23\u7684\uff0c\u4f46\u807d\u8d77\u4f86\u7684\u611f\u89ba\u537b\u622a\u7136\u4e0d\u540c\u3002<\/p>\n<\/li>\n

  17. \n

    \u9078\u64c7\u6027\u95dc\u6ce8 (Selective Perception)<\/strong>
    \n\u6234\u8457\u6709\u8272\u773c\u93e1\u53bb\u89c0\u5bdf\u4e8b\u7269\uff0c\u5728\u653f\u6cbb\u7684\u5834\u57df\u4e2d\u66f4\u662f\u5e38\u898b\uff0c\u5169\u65b9\u660e\u660e\u505a\u7684\u662f\u540c\u6a23\u6216\u5dee\u4e0d\u591a\u7684\u4e8b\u60c5\uff0c\u96d9\u65b9\u652f\u6301\u8005\u537b\u53ea\u770b\u7684\u5230\u5c0d\u65b9\u7684\u7f3a\u9ede\u8207\u5df1\u65b9\u7684\u512a\u9ede\u3002<\/p>\n<\/li>\n

  18. \n

    \u523b\u677f\u5370\u8c61 (Stereotyping)<\/strong>
    \n\u7cbe\u78ba\u7684\u5b9a\u7fa9\u662f\u5728\u5c0d\u7279\u5b9a\u7684\u4eba\u4e8b\u7269\u63a5\u89f8\u524d\uff0c\u5c31\u76f4\u63a5\u628a\u5c0d\u5176\u6240\u5c6c\u7fa4\u9ad4\u7684\u65e2\u5b9a\u5370\u8c61\u5957\u7528\u5728\u4e0a\u9762\u3002\u5728\u5927\u591a\u6642\u5019\u523b\u677f\u5370\u8c61\u80fd\u8b93\u6211\u5011\u5c0d\u63a5\u4e0b\u4f86\u8981\u767c\u751f\u7684\u4e8b\u7269\u6709\u6240\u6e96\u5099\uff0c\u4f46\u4e5f\u53ef\u80fd\u6703\u5931\u53bb\u6539\u8b8a\u8a8d\u77e5\u7684\u6a5f\u6703\u3002<\/p>\n<\/li>\n

  19. \n

    \u5016\u5b58\u8005\u504f\u8aa4 (Survivorship bias)<\/strong>
    \n\u53ea\u6ce8\u610f\u5230\u90a3\u4e9b\u6210\u529f\u8005\uff0c\u5831\u7ae0\u5a92\u9ad4\u4e2d\u66f4\u662f\u5e38\u898b\uff0c\u6bd4\u65b9\u8aaa\u5e38\u770b\u5230\u5275\u696d\u6210\u529f\u7684\u5831\u5c0e\u6848\u4f8b\uff0c\u537b\u5ffd\u7565\u4e86\u5176\u5be6\u5275\u696d\u662f\u6709\u9ad8\u905490%\u4ee5\u4e0a\u7684\u5931\u6557\u6a5f\u6703\uff0c\u800c\u9019\u4e9b\u4f54\u591a\u6578\u7684\u5931\u6557\u8005\u662f\u6c92\u6709\u8cc7\u683c\u51fa\u73fe\u5728\u5831\u5c0e\u4e2d\u7684\u3002<\/p>\n<\/li>\n

  20. \n

    \u96f6\u98a8\u96aa\u504f\u8aa4 (Zero-risk bias)<\/strong>
    \n\u4eba\u985e\u56e0\u70ba\u98a8\u96aa\u8da8\u907f\u7684\u7279\u6027\u50be\u5411\u5b8c\u5168\u6d88\u9664\u4e0d\u78ba\u5b9a\u6027\uff0c\u6bd4\u65b9\u8aaa\u73fe\u5728\u6709\u5169\u500b\u89e3\u6c7a\u65b9\u6848\u90fd\u8981\u50f9\u4e94\u842c\uff0c\u4e00\u500b\u53ef\u4ee5\u628a\u96f6\u4ef6A\u7684\u4e0d\u826f\u7387\u5f9e5%\u964d\u52302%\uff0c\u53e6\u4e00\u500b\u5247\u53ef\u4ee5\u628a\u96f6\u4ef6B\u7684\u4e0d\u826f\u7387\u5f9e1%\u964d\u52300%\uff0c\u90a3\u9ebc\u4eba\u5011\u6703\u50be\u5411\u5f8c\u8005\uff0c\u56e0\u70ba\u4eba\u5011\u66f4\u504f\u597d\u65bc\u5b8c\u5168\u96f6\u98a8\u96aa\u2500\u5373\u4fbf\u6c92\u6709\u7d93\u6fdf\u6548\u76ca\u53ef\u8a00\u3002<\/p>\n<\/li>\n<\/ol>\n

    \"\"<\/a><\/p>\n

    \n

    \u53c3\u8003\u8cc7\u6e90<\/h3>\n
      \n
    1. Medium\u597d\u8b80\u7248\uff1ahttp:\/\/bit.ly\/3jQpFtu<\/a> <\/li>\n
    2. https:\/\/lkm543.medium.com\/20%E7%A8%AE%E5%B8%B8%E8%A6%8B%E7%9A%84%E8%AA%8D%E7%9F%A5%E5%81%8F%E8%AA%A4-9d00d0acb5d0<\/a><\/li>\n
    3. Ref: https:\/\/apus.libanswers.com\/faq\/191117<\/a><\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"

      \u53bb\u5e74\u6216\u524d\u5e74\u66fe\u7d93\u770b\u904e\u7684\u6587\u7ae0\uff0c\u4f86\u4e0d\u53ca\u505a\u7b46\u8a18\uff0c\u4eca\u5929\u5f37\u8feb\u81ea\u5df1\u628a\u4ed6\u5011\u8a18\u4e0b\u4f86\u3002 \u3010\u641e\u7838\u4f60\u6c7a\u7b56\u7684 Continue reading \u3010\u7b46\u8a18\u3011\u641e\u7838\u4f60\u6c7a\u7b56\u7684 20 \u7a2e\u8a8d\u77e5\u504f\u8aa4<\/span>→<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-3358","post","type-post","status-publish","format-standard","hentry","category-4"],"_links":{"self":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3358","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3358"}],"version-history":[{"count":9,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3358\/revisions"}],"predecessor-version":[{"id":3374,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3358\/revisions\/3374"}],"wp:attachment":[{"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3358"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3358"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/yowlab.idv.tw\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3358"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}