Problems with Sampling · 抽样的潜在问题
| English | 中文 | Pinyin · 拼音 |
|---|---|---|
| undercoverage/ˌʌndəˈkʌvərɪdʒ/ | 覆盖不足 | fù gài bù zú |
| voluntary response/ˈvɒləntəri rɪˈspɒns/ | 自愿回应 | zì yuàn huí yìng |
| nonresponse/ˌnɒnrɪˈspɒns/ | 无回应 | wú huí yìng |
| response bias/rɪˈspɒns ˈbaɪəs/ | 回应偏差 | huí yìng piān chā |
| question wording bias/ˈkwestʃn ˈwɜːdɪŋ ˈbaɪəs/ | 问题措辞偏差 | wèn tí cuò cí piān chā |
Who gets left out?
- Even with a plan, sampling can go wrong — usually by missing or distorting responses.
- Undercoverage 覆盖不足: part of the population has no chance of being chosen.
- Example: a phone survey misses everyone without a phone.
- The reached group then over-represents whoever was reachable.
谁被漏掉了？
- 即使有计划，抽样也可能出错——通常是漏掉或扭曲回应。
- **覆盖不足：**总体的一部分根本没有机会被选中。
- 例如：电话调查会漏掉所有没有电话的人。
- 被触及的群体于是过度代表了那些本就能被触及的人。
Voluntary response
- Voluntary response 自愿回应: people choose themselves into the sample (call-ins, web polls).
- Those with strong opinions volunteer most, so the result is skewed.
- It's a self-selected group, not a random one — reliably biased.
- More volunteers doesn't help; they're the same lopsided crowd.
自愿回应
- **自愿回应：**人们自己选择进入样本（来电、网络投票）。
- 意见强烈的人最爱主动参与，所以结果被扭曲。
- 这是一个自我选择的群体，而非随机的——必然有偏。
- 更多志愿者也无济于事；他们是同一群偏斜的人。
Nonresponse and response bias
- Nonresponse 无回应: selected people can't or won't answer; the answerers may differ from the silent.
- Response bias 回应偏差: people answer, but untruthfully — to look good, or to please the interviewer.
- Sensitive topics (income, habits) invite dishonest answers.
- Both distort results even when the sampling was random.
无回应与回应偏倚
- **无回应：**被选中的人无法或不愿回答；回答者可能与沉默者不同。
- 回应偏倚：人们回答了，但不诚实——为了显得体面，或为了取悦访问者。
- 敏感话题（收入、习惯）会诱发不诚实的回答。
- 即便抽样是随机的，这两者也会扭曲结果。
Question wording
- Question wording bias 问题措辞偏差: a leading or confusing question pushes answers one way.
- "Don't you agree the unfair tax should be cut?" is not neutral.
- The wording, not the respondents' true views, drives the result.
- Neutral, clear wording is part of good design.
问题措辞
- **措辞偏倚：**引导性或令人困惑的问题把回答推向某一方。
- “你难道不同意应该削减这项不公平的税吗？”并不中立。
- 是措辞、而非受访者的真实看法，在驱动结果。
- 中立、清晰的措辞是好设计的一部分。
A bigger sample does not fix any of these — they are bias, not random error. Undercoverage, voluntary response, nonresponse, response bias, and loaded wording all come from a flawed method, so collecting more the same way just cements the wrong answer. Fix the method, not the size.
更大的样本无法修复这些之中的任何一个——它们是偏倚，而非随机误差。覆盖不足、自愿回应、无回应、回应偏倚和带倾向的措辞，都源自有缺陷的方法，所以用同样方式收集更多，只会把错误答案坐实。要修的是方法，而不是规模。
A website posts: "Should the mayor resign? Click to vote."
- Voluntary response: only angry visitors bother to click → biased.
- Undercoverage: people who never visit the site have no voice.
- Adding millions of clicks doesn't make it representative.
一个网站贴出：“市长应该辞职吗？点击投票。”
- **自愿回应：**只有愤怒的访客才会去点 → 有偏。
- **覆盖不足：**从不访问该网站的人没有发言权。
- 增加几百万次点击也不会让它有代表性。
Sampling bias creeps in through undercoverage (some can't be chosen), voluntary response (self-selection), nonresponse (selected people don't answer), response bias (untruthful answers), and question wording bias. None is cured by a larger sample — only by a better method.
抽样偏倚通过以下方式渗入：覆盖不足（有些人无法被选）、自愿回应（自我选择）、无回应（被选中者不回答）、回应偏倚（不诚实的回答）和措辞偏倚。没有一个能靠更大的样本治好——只能靠更好的方法。
A distorted response mix · 被扭曲的回应构成
Voluntary response over-represents the strongly opinionated. · 自愿回应过度代表了意见强烈的人。
A phone survey never reaches people without phones. This is... · 一项电话调查永远触及不到没有电话的人。这是……
Part of the population has no chance of selection — undercoverage. · 总体的一部分没有机会被选中——覆盖不足。
People answer a survey about drinking untruthfully to look responsible. This is... · 人们在关于饮酒的调查中不诚实作答以显得负责。这是……
Untruthful answering is response bias. · 不诚实作答是回应偏倚。
A leading question like 'Don't you agree the unfair tax should be cut?' causes question wording bias. · 像“你难道不同意应削减这项不公平的税吗？”这样的引导性问题会造成措辞偏倚。
Loaded wording pushes answers one way. · 带倾向的措辞把回答推向一方。
When people self-select into a poll (like a call-in), it is called ___ response bias (one word). · 当人们自我选择进入一个投票（如来电投票），这叫 ___ 回应偏倚（填英文一词）。
Self-selection = voluntary response. · 自我选择 = 自愿回应。
Increasing the sample size will fix bias caused by a flawed sampling method. · 增大样本量能修复由有缺陷的抽样方法造成的偏倚。
Bias isn't cured by size — only by a better method. · 偏倚不靠规模治好——只靠更好的方法。