ArticleslgStudy

science

Split normal distribution

Split normal distribution 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 Split normal distribution rather than just read about it. In short: In probability theory and statistics, the split normal distribution also known as the two-piece normal distribution results from joining at the mode the corresponding halves of two normal distributions with the same mode but different variances. It is claimed by Johnson et al. that this distribution was introduced by Gibbons and Mylroie and by John.

Key takeaways

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

Reference excerpt

In probability theory and statistics, the split normal distribution also known as the two-piece normal distribution results from joining at the mode the corresponding halves of two normal distributions with the same mode but different variances. It is claimed by Johnson et al. that this distribution was introduced by Gibbons and Mylroie and by John. But these are two of several independent rediscoveries of the Zweiseitige Gauss'sche Gesetz introduced in the posthumously published Kollektivmasslehre (1897) of Gustav Theodor Fechner (1801-1887), see Wallis (2014). Another rediscovery has appeared more recently in a finance journal.

Definition The split normal distribution arises from merging two opposite halves of two probability density functions (PDFs) of normal distributions in their common mode. The PDF of the split normal distribution is given by

f ( x ; μ , σ 1 , σ 2 ) = { A exp ⁡ ( − ( x − μ ) 2 2 σ 1 2 ) if x < μ A exp ⁡ ( − ( x − μ ) 2 2 σ 2 2 ) otherwise {\displaystyle f(x;\mu ,\sigma _{1},\sigma _{2})={\begin{cases}A\exp \left(-{\dfrac {(x-\mu )^{2}}{2\sigma _{1}^{2}}}\right)&{\text{if }}x<\mu \\[1ex]A\exp \left(-{\dfrac {(x-\mu )^{2}}{2\sigma _{2}^{2}}}\right)&{\text{otherwise}}\end{cases}}}

where

A = 2 / π ( σ 1 + σ 2 ) − 1 . {\displaystyle \quad A={\sqrt {2/\pi }}(\sigma _{1}+\sigma _{2})^{-1}.}

Discussion The split normal distribution results from merging two halves of normal distributions. In a general case the 'parent' normal distributions can have different variances which implies that the joined PDF would not be continuous. To ensure that the resulting PDF integrates to 1, the normalizing constant A is used. In a special case when σ 1 2 = σ 2 2 = σ ∗ 2 {\displaystyle \sigma _{1}^{2}=\sigma _{2}^{2}=\sigma _{*}^{2}} the split normal distribution reduces to normal distribution with variance σ ∗ 2 {\displaystyle \sigma _{*}^{2}} . When σ2≠σ1 the constant A is different from the constant of normal distribution. However, when σ 1 2 = σ 2 2 = σ ∗ 2 {\displaystyle \sigma _{1}^{2}=\sigma _{2}^{2}=\sigma _{*}^{2}} the constants are equal. The sign of its third central moment is determined by the difference (σ2-σ1). If this difference is positive, the distribution is skewed to the right and if negative, then it is skewed to the left. Other properties of the split normal density were discussed by Johnson et al. and Julio.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Split normal distribution

Start with the simplest possible case. Write down what Split normal distribution 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 Split normal distribution 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 Split normal distribution 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 Split normal distribution

In research
Split normal distribution 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 Split normal distribution 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
Split normal distribution is common in secondary-school and first-year university syllabi. It links to neighbouring topics Continuous distributions, Normal distribution, so understanding it makes those chapters shorter.
In everyday life
Look for Split normal distribution 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.

Affiliate

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

How to study Split normal distribution in 20 minutes

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

Frequently asked questions

What is Split normal distribution in simple terms?

In probability theory and statistics, the split normal distribution also known as the two-piece normal distribution results from joining at the mode the corresponding halves of two normal distributions with the same mode but different variances. It is claimed by Johnson et al. that this distributio…

Why does Split normal distribution 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 Split normal distribution?

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 Split normal distribution.

Tags

  • Continuous distributions
  • Normal distribution

Keep exploring