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Research draft

random variable

vr.tr.random-variable · XCT.QLT

Let an agent define random variables and their kinds, explain distributions, expectation and independence, relate the concept to statistics and modelling, and separate the concept from unrelated aliases in the registry entry.

Thing Registry Cross-cutting context

Research draft, second pass

A second pass drafted this model: the structure a model of this thing needs, and what is known about it in the world. The line under this one says how the second half was obtained - researched against sources, or recalled without web access, in which case nothing here was read anywhere and every claim is a lead to verify. Unreviewed either way.

written by Claude from model knowledge without web access - no source was read, every claim is a lead to verify

Researched by: Claude

Purpose and description

Let an agent define random variables and their kinds, explain distributions, expectation and independence, relate the concept to statistics and modelling, and separate the concept from unrelated aliases in the registry entry.

A variable whose value is determined by the outcome of a random experiment, formally a measurable function from a probability space to a set of values, usually real numbers, with a distribution describing the probabilities of its values; random variables are discrete, continuous or mixed, may be real, complex or vector valued, and are the basic objects of probability and statistics, with quantities such as the sample standard deviation being random variables computed from data.

What it is for: Modelling uncertain quantities.

It can be define the concept and kinds; explain distributions and moments; relate to statistics and modelling; separate unrelated aliases.

Distinguishing features

Measurable function on a probability space

Distribution and moments

Independence and dependence

Foundation of statistics

What it looks like

Not a visible object; a symbol such as X with a distribution.

How it is recognised

Value determined by a random outcome

Discrete, continuous, real, complex or vector valued

A parameter is fixed; a statistic is a random variable computed from a sample

Related models

is a kind of - real-valued case

random element

is a kind of - in registry terms

variable

has - its law

probability distribution

is studied by - the discipline

probability theory

In practice

Families and kinds

discrete random variables

continuous random variables

complex and vector-valued random variables

statistics such as the sample mean and sample standard deviation

projections and decompositions such as the Hajek projection

random elements in general spaces

Standards and regulation

ISO 3534 statistics vocabulary

Notation conventions in probability texts

Failure modes and hazards

Confusing a random variable with its realisation or its distribution

Assuming independence without justification

Sense confusion with unrelated aliases such as capsule toys

Also called

capsule toycomplex random variablediscrete random variableHajek projectionsample standard deviationconfoundingcontinuous random variablecentred random variablestandardized sample random variablecentered variableRandom closed setidentically distributedmoderationindependent random variablesreal random variablehitting time

Where this came from

wikidata · CC0 1.0

Drafted structure

Bundle to layer to finding to question, as the second pass will find it: 4 bundles · 8 layers · 8 findings · 16 questions.

Define What a random variable is.

Definition.

Definition

Definition and kinds.

Definition

Definition.

  1. What is a random variable, formally and intuitively, and what kinds exist? definition
  2. Is the question about a random variable, its distribution, a realisation or a parameter? boundary

Distribution

Distributions.

Distribution

Distribution.

  1. How are distributions, densities and mass functions attached to random variables? definition
  2. Which entry fits probability distribution? action
Compute Moments and transformations.

Computation.

Moments

Expectation and variance.

Moments

Moments.

  1. How are expectation, variance and other moments computed? action
  2. What are the values for the variable in question? measurement

Transform

Functions of random variables.

Transform

Transform.

  1. How are sums, products and functions of random variables handled? action
  2. Which entry fits convolution of distributions? action
Relations Independence and dependence.

Theory.

Independence

Independence.

Independence

Independence.

  1. What do independence, correlation and conditioning mean for random variables? provenance
  2. Which references are standard? provenance

Limits

Limit theorems.

Limits

Limits.

  1. What do the law of large numbers and central limit theorem say about sequences of random variables? provenance
  2. Which entry fits the central limit theorem? action
Apply Statistics and modelling.

Application.

Statistics

Statistics as random variables.

Statistics

Statistics.

  1. How are sample statistics such as the standard deviation random variables, and why does it matter? provenance
  2. Which entry fits statistic? action

Teach

Teaching.

Teach

Teaching.

  1. How are random variables taught, and which misconceptions arise? provenance
  2. Which entry fits statistics education? action

What the second pass must settle

  • Should discrete and continuous random variables be separate entries?
  • How should probability references be linked?
  • The registry entry has merged aliases for unrelated concepts such as capsule toys and confounding; should they be removed?