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Somers' D

Somers' D is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Somers' D rather than just read about it. In short: In statistics, Somers’ D, sometimes incorrectly referred to as Somer’s D, is a measure of ordinal association between two possibly dependent random variables X and Y. Somers’ D takes values between − 1 {\displaystyle -1} when all pairs of the variables disagree and 1 {\displaystyle 1} when all pairs of the variables agree.

Key takeaways

  • Somers' D belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Somers' D to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Somers' D from memory before moving on to harder problems.

Reference excerpt

In statistics, Somers’ D, sometimes incorrectly referred to as Somer’s D, is a measure of ordinal association between two possibly dependent random variables X and Y. Somers’ D takes values between − 1 {\displaystyle -1} when all pairs of the variables disagree and 1 {\displaystyle 1} when all pairs of the variables agree. Somers’ D is named after Robert H. Somers, who proposed it in 1962. Somers’ D plays a central role in rank statistics and is the parameter behind many nonparametric methods. It is also used as a quality measure of binary choice or ordinal regression (e.g., logistic regressions) and credit scoring models.

Somers’ D for sample We say that two pairs ( x i , y i ) {\displaystyle (x_{i},y_{i})} and ( x j , y j ) {\displaystyle (x_{j},y_{j})} are concordant if the ranks of both elements agree, or x i > x j {\displaystyle x_{i}>x_{j}} and y i > y j {\displaystyle y_{i}>y_{j}} or if x i < x j {\displaystyle x_{i}<x_{j}} and y i < y j {\displaystyle y_{i}<y_{j}} . We say that two pairs ( x i , y i ) {\displaystyle (x_{i},y_{i})} and ( x j , y j ) {\displaystyle (x_{j},y_{j})} are discordant, if the ranks of both elements disagree, or if x i > x j {\displaystyle x_{i}>x_{j}} and y i < y j {\displaystyle y_{i}<y_{j}} or if x i < x j {\displaystyle x_{i}<x_{j}} and y i > y j {\displaystyle y_{i}>y_{j}} . If x i = x j {\displaystyle x_{i}=x_{j}} or y i = y j {\displaystyle y_{i}=y_{j}} , the pair is neither concordant nor discordant. Let ( x 1 , y 1 ) , ( x 2 , y 2 ) , … , ( x n , y n ) {\displaystyle (x_{1},y_{1}),(x_{2},y_{2}),\ldots ,(x_{n},y_{n})} be a set of observations of two possibly dependent random vectors X and Y. Define Kendall tau rank correlation coefficient τ {\displaystyle \tau } as

τ = N C − N D n ( n − 1 ) / 2 , {\displaystyle \tau ={\frac {N_{C}-N_{D}}{n(n-1)/2}},}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Somers' D

Start with the simplest possible case. Write down what Somers' D claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Somers' D before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Somers' D ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Somers' D

In research
Somers' D appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Somers' D in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Somers' D is common in secondary-school and first-year university syllabi. It links to neighbouring topics Independence (probability theory), Nonparametric statistics, so understanding it makes those chapters shorter.
In everyday life
Look for Somers' D outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Somers' D in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Somers' D means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Somers' D out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Somers' D in simple terms?

In statistics, Somers’ D, sometimes incorrectly referred to as Somer’s D, is a measure of ordinal association between two possibly dependent random variables X and Y. Somers’ D takes values between − 1 {\displaystyle -1} when all pairs of the variables disagree and 1 {\displaystyle 1} when all pair…

Why does Somers' D matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Somers' D?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Somers' D.

Tags

  • Independence (probability theory)
  • Nonparametric statistics

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