Alphabeta Math
TheoremStatement: Literature-sourcedProof: AI-adaptedSession-authored (Fable 5 assisted)precheck passaudited 2026-08-13
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Expectation is linear for every finite family of random variables, without any independence hypothesis

Statement

For a finite family of real random variables (Xi)iI on one finite probability space and real scalars (ai)iI, E ⁣[iIaiXi]=iIaiE[Xi]. No independence hypothesis is required. For I=, both sides are 0.

Facts & Assumptions

Given: A finite probability space, random variables Xi, and real scalars ai, indexed by a finite set I.

[L1]

Expectation is a finite weighted sum over outcomes (Expectation of a real random variable on a finite probability space).

[L2]

Finite sums are additive and compatible with real scaling (Laws of finite sums and finite products).

Proof

technique · direct
1.1

Expanding the left side gives ωΩiIaiXi(ω)w(ω).

L1
2.1

Finite Fubini and distributivity turn step 1.1 into iIaiωΩXi(ω)w(ω)=iIaiE[Xi].

step 1.1L2L3algebra
3.1

The calculation uses no independence identity. If I=, the two sums in step 2.1 are empty and equal 0.

step 2.1

Depends on

Used by

Dependency tree · next 3 levels

Direct dependencies and their dependencies through the next three levels: 55 results over 18 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.

Sources