ArticleslgStudy

science

Stolarsky mean

Stolarsky mean is a science 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 Stolarsky mean rather than just read about it. In short: In mathematics, the Stolarsky mean is a generalization of the logarithmic mean. It was introduced by Kenneth B.

Key takeaways

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

Reference excerpt

In mathematics, the Stolarsky mean is a generalization of the logarithmic mean. It was introduced by Kenneth B. Stolarsky in 1975.

Definition For two positive real numbers x {\displaystyle x} and y {\displaystyle y} the Stolarsky Mean is defined as:

S p ( x , y ) = { x , if x = y , ( x p − y p p ( x − y ) ) 1 / ( p − 1 ) , otherwise . {\displaystyle S_{p}(x,y)=\left\{{\begin{array}{l l}x,&{\text{if }}x=y,\\\left({\frac {x^{p}-y^{p}}{p(x-y)}}\right)^{1/(p-1)},&{\text{otherwise}}.\end{array}}\right.}

Derivation It is derived from the mean value theorem, which states that a secant line, cutting the graph of a differentiable function f {\displaystyle f} at ( x , f ( x ) ) {\displaystyle (x,f(x))} and ( y , f ( y ) ) {\displaystyle (y,f(y))} , has the same slope as a line tangent to the graph at some point ξ {\displaystyle \xi } in the interval [ x , y ] {\displaystyle [x,y]} .

∃ ξ ∈ [ x , y ] f ′ ( ξ ) = f ( x ) − f ( y ) x − y {\displaystyle \exists \xi \in [x,y]\ f'(\xi )={\frac {f(x)-f(y)}{x-y}}}

The Stolarsky mean is obtained by

ξ = [ f ′ ] − 1 ( f ( x ) − f ( y ) x − y ) {\displaystyle \xi =\left[f'\right]^{-1}\left({\frac {f(x)-f(y)}{x-y}}\right)}

when choosing f ( x ) = x p {\displaystyle f(x)=x^{p}} .

Special cases

lim p → − ∞ S p ( x , y ) {\displaystyle \lim _{p\to -\infty }S_{p}(x,y)} is the minimum.

S − 1 ( x , y ) {\displaystyle S_{-1}(x,y)} is the geometric mean.

lim p → 0 S p ( x , y ) {\displaystyle \lim _{p\to 0}S_{p}(x,y)} is the logarithmic mean. It can be obtained from the mean value theorem by choosing f ( x ) = ln ⁡ x {\displaystyle f(x)=\ln x} .

S 1 2 ( x , y ) {\displaystyle S_{\frac {1}{2}}(x,y)} is the power mean with exponent 1 2 {\displaystyle {\frac {1}{2}}} .

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Stolarsky mean

Start with the simplest possible case. Write down what Stolarsky mean claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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 Stolarsky mean 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 Stolarsky mean 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 Stolarsky mean

In research
Stolarsky mean appears in science 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 Stolarsky mean 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
Stolarsky mean is common in secondary-school and first-year university syllabi. It links to neighbouring topics Means, so understanding it makes those chapters shorter.
In everyday life
Look for Stolarsky mean 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.
Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Stolarsky mean” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Stolarsky mean in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Stolarsky mean 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 Stolarsky mean out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Stolarsky mean in simple terms?

In mathematics, the Stolarsky mean is a generalization of the logarithmic mean. It was introduced by Kenneth B.

Why does Stolarsky mean matter?

Because it connects several science 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 Stolarsky mean?

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 Stolarsky mean.

Tags

  • Means

Keep exploring