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中級實務應用·9 min

利用標準差偵測離群值

學習如何使用標準差識別資料中的離群值。掌握三個標準差法則、IQR 方法,並了解何時應該移除離群值。

什麼是離群值?

離群值是與其他觀測值明顯不同的資料點。它們可能是由測量誤差、資料輸入錯誤造成的,也可能代表值得深入調查的特殊案例。

位於 (10, 50) 的橘色點就是一個離群值

三個標準差法則

對於常態分配的資料,超出平均數 3 個標準差之外的資料點被視為離群值。這種情況在隨機條件下出現的機率不到 0.3%。

離群值判定條件

x < μ - 3σ OR x > μ + 3σ

範例

假設考試成績 μ = 75,σ = 10: - 下界:75 - 30 = 45 - 上界:75 + 30 = 105 - 低於 45 分或高於 105 分的成績即為離群值

Z 分數法

計算每個資料點的 Z 分數。如果 |z| > 3(有時使用 2.5),則視為離群值。

Z 分數

z = (x - μ) / σ

閾值選項

- |z| > 3:保守標準(偵測較少離群值) - |z| > 2.5:中等標準 - |z| > 2:寬鬆標準(偵測較多離群值)

IQR 方法(替代方案)

四分位距 (IQR) 方法對離群值有更好的抵抗力,因為它不使用平均數或標準差。

1

步驟一

找出 Q1(第 25 百分位數)和 Q3(第 75 百分位數)
2

步驟二

計算 IQR = Q3 - Q1
3

步驟三

下界 = Q1 - 1.5 × IQR
4

步驟四

上界 = Q3 + 1.5 × IQR
5

步驟五

超出上下界的點即為離群值

如何處理離群值

不要自動刪除!

離群值不一定是錯誤。在移除之前,請先調查: - 是否為資料輸入或測量錯誤? - 是否為真實存在的極端值? - 是否代表一個重要的邊界情況?

何時移除

- 已確認的資料輸入錯誤 - 測量設備故障 - 超出數值可能範圍

何時保留

- 代表真實的變異性 - 對你的分析很重要 - 移除會導致結果偏差

Further Reading

How to Read This Article

A statistics tutorial is a practical interpretation guide, not just a formula dump. It refers to the assumptions, notation, and reporting language that analysts need when they explain a result to a teacher, manager, client, or reviewer. The article body covers the specific topic, while the sections below create a common interpretation frame that readers can reuse across related metrics.

Reading goalWhat to focus onCommon mistake
DefinitionWhat the metric is and what quantity it summarizesTreating the formula as self-explanatory
Formula choiceSample versus population assumptions and notationUsing n when n-1 is required or vice versa
InterpretationWhether the result indicates concentration, spread, or riskCalling a large value good or bad without context

Frequently Asked Questions

How should I interpret a high standard deviation?

A high standard deviation means the observations are spread farther from the mean on average. Whether that spread is acceptable depends on the context: wide dispersion might signal risk in finance, instability in manufacturing, or genuine natural variation in scientific data.

Why do some articles mention n while others mention n-1?

The denominator reflects the difference between population and sample formulas. Population variance and population standard deviation use N because the full dataset is known. Sample variance and sample standard deviation often use n-1 because Bessel’s correction reduces bias when estimating population spread from a sample.

What is a statistical interpretation guide?

A statistical interpretation guide is a page that moves beyond arithmetic and explains meaning. It tells you what a metric is, when the formula applies, and how to describe the result in plain English without overstating certainty.

Can I cite this article in a report?

You should cite the underlying authoritative reference for formal work whenever possible. This page is best used as an explanatory bridge that helps you understand the concept before quoting the original standard or handbook.

Why include direct citations on every article page?

Direct citations give readers a route to verify the definition, notation, and assumptions. That improves trust and reduces the chance that a simplified explanation is mistaken for the entire technical standard.

Authoritative References

These sources define the concepts referenced most often across our articles. Bessel's correction is a sample adjustment, variance is a squared measure of spread, and standard deviation is the square root of variance expressed in the same units as the data.