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SDCalc
入門概念·6 min

68-95-99.7の経験則を徹底解説

正規分布における経験則(68-95-99.7ルール)をマスター。標準偏差を使って確率を素早く推定し、外れ値を特定する方法を学びましょう。

経験則とは?

経験則(68-95-99.7ルールまたは3シグマルールとも呼ばれます)は、正規分布において平均から標準偏差1つ分、2つ分、3つ分の範囲に含まれるデータの割合を覚えるための目安です。

68%

±1σの範囲内

95%

±2σの範囲内

99.7%

±3σの範囲内

視覚的な解説

The Classic Bell Curve

範囲割合
μ ± 1σ68.27%
μ ± 2σ95.45%
μ ± 3σ99.73%

実用的な応用

  • 確率の素早い推定:複雑な計算をしなくても、データの約95%が平均から標準偏差2つ分以内に収まると推定できます。
  • 外れ値の検出:3σを超えるデータ点は偶然に発生する確率が0.3%未満であり、調査に値する統計的外れ値といえます。
  • 品質管理:シックスシグマ手法では、この法則を使って品質の閾値を設定し、工程のばらつきを特定します。

計算例

例:SAT試験の成績

SAT試験の成績は、μ = 1050、σ = 200 の正規分布に従います。 - 68% の受験者は850~1250の範囲(±1σ) - 95% の受験者は650~1450の範囲(±2σ) - 99.7% の受験者は450~1650の範囲(±3σ) 1450点以上のスコアは、受験者全体の上位約2.5%に入ります。

限界と注意点

正規分布にのみ適用される

経験則は、正規(ガウス)分布に従うデータにのみ適用されます。歪んだデータや非正規データには、これらの割合は当てはまりません。この法則を使用する前に、必ずデータが正規分布に従っているか確認してください。

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.