Question 4530: Variance of a Shared-Model Difference

Original question and givens

S={0,…,2}, F=P(S), masses=[5, 2, 1], D=8, and w_i=mass_i/D. Masses are nonnegative and sum exactly to D; uniform weights are not assumed. X=[-4, 2, 5] in index order and Y=[1, -1, -4] on the same S and weights, with no independence premise. Find Var(X−Y), not Var(X)+Var(Y). Use exact reduced fractions with positive denominators, retaining /1 for integers.

• G001 — S={0,…,2}, F=P(S), masses=[5, 2, 1], D=8, and w_i=mass_i/D. Masses are nonnegative and sum exactly to D; uniform weights are not assumed. X=[-4, 2, 5] in index order and Y=[1, -1, -4] on the same S and weights, with no independence premise. Find Var(X−Y), not Var(X)+Var(Y). Use exact reduced fractions with positive denominators, retaining /1 for integers.

Definition and scope

Use the original question domain, assumptions and cited MKO definitions. This item has second-context mathematical and bilingual review, with the model, answer and every arithmetic step independently recomputed from the original parameters; the source question remains a candidate.

• mko-variance

Step-by-step derivation

total mass numerator := sum(5, 2, 1)

total mass numerator = 8

probability weight0 := div(5, 8)

probability weight0 = 5/8

probability weight1 := div(2, 8)

probability weight1 = 1/4

probability weight2 := div(1, 8)

probability weight2 = 1/8

values=[-4, 2, 5];weights=[5/8, 1/4, 1/8]

known finite probability law,not a sampled estimate

pointwise difference0 := sub(-4, 1)

pointwise difference0 = -5

pointwise difference1 := sub(2, -1)

pointwise difference1 = 3

pointwise difference2 := sub(5, -4)

pointwise difference2 = 9

[-5, 3, 9]

compute the variance of this shared-model difference

target variable weighted value0 := mul(5/8, -5)

target variable weighted value0 = -25/8

target variable weighted value1 := mul(1/4, 3)

target variable weighted value1 = 3/4

target variable weighted value2 := mul(1/8, 9)

target variable weighted value2 = 9/8

target variable mean := sum(-25/8, 3/4, 9/8)

target variable mean = -5/4

centered difference0 := sub(-5, -5/4)

centered difference0 = -15/4

centered square0 := square(-15/4)

centered square0 = 225/16

centered contribution0 := mul(5/8, 225/16)

centered contribution0 = 1125/128

centered difference1 := sub(3, -5/4)

centered difference1 = 17/4

centered square1 := square(17/4)

centered square1 = 289/16

centered contribution1 := mul(1/4, 289/16)

centered contribution1 = 289/64

centered difference2 := sub(9, -5/4)

centered difference2 = 41/4

centered square2 := square(41/4)

centered square2 = 1681/16

centered contribution2 := mul(1/8, 1681/16)

centered contribution2 = 1681/128

[1125/128, 289/64, 1681/128]

all indexed centered-square contributions retained

variance of the difference := sum(1125/128, 289/64, 1681/128)

variance of the difference = 423/16

Reverse checks

• S024 · premise_and_result_audit — Recompute variance of the difference with exact rational arithmetic, not rounded decimals.
• S023 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.
• S022 · premise_and_result_audit — Recompute centered contribution2 with exact rational arithmetic, not rounded decimals.
• S021 · premise_and_result_audit — Recompute centered square2 with exact rational arithmetic, not rounded decimals.
• S020 · premise_and_result_audit — Recompute centered difference2 with exact rational arithmetic, not rounded decimals.
• S019 · premise_and_result_audit — Recompute centered contribution1 with exact rational arithmetic, not rounded decimals.
• S018 · premise_and_result_audit — Recompute centered square1 with exact rational arithmetic, not rounded decimals.
• S017 · premise_and_result_audit — Recompute centered difference1 with exact rational arithmetic, not rounded decimals.
• S016 · premise_and_result_audit — Recompute centered contribution0 with exact rational arithmetic, not rounded decimals.
• S015 · premise_and_result_audit — Recompute centered square0 with exact rational arithmetic, not rounded decimals.
• S014 · premise_and_result_audit — Recompute centered difference0 with exact rational arithmetic, not rounded decimals.
• S013 · premise_and_result_audit — Recompute target variable mean with exact rational arithmetic, not rounded decimals.
• S012 · premise_and_result_audit — Recompute target variable weighted value2 with exact rational arithmetic, not rounded decimals.
• S011 · premise_and_result_audit — Recompute target variable weighted value1 with exact rational arithmetic, not rounded decimals.
• S010 · premise_and_result_audit — Recompute target variable weighted value0 with exact rational arithmetic, not rounded decimals.
• S009 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.
• S008 · premise_and_result_audit — Recompute pointwise difference2 with exact rational arithmetic, not rounded decimals.
• S007 · premise_and_result_audit — Recompute pointwise difference1 with exact rational arithmetic, not rounded decimals.
• S006 · premise_and_result_audit — Recompute pointwise difference0 with exact rational arithmetic, not rounded decimals.
• S005 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.
• S004 · premise_and_result_audit — Recompute probability weight2 with exact rational arithmetic, not rounded decimals.
• S003 · premise_and_result_audit — Recompute probability weight1 with exact rational arithmetic, not rounded decimals.
• S002 · premise_and_result_audit — Recompute probability weight0 with exact rational arithmetic, not rounded decimals.
• S001 · premise_and_result_audit — Recompute total mass numerator with exact rational arithmetic, not rounded decimals.

Result

423/16

The full substitutions and premise checks give the original answer; source identity,format and status are unchanged.

This question review and source binding

Review date: 2026-10-26

Original questions, answers, step expressions, numeric ASTs and historical records are retained. Source candidate labels remain historical and are not overwritten as formal proof.