Question 4527: Variance of a Shared-Model Difference

Original question and givens

S={0,…,1}, F=P(S), masses=[1, 1], D=2, and w_i=mass_i/D. Masses are nonnegative and sum exactly to D; uniform weights are not assumed. X=[0, 2] in index order and Y=[2, 0] 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,…,1}, F=P(S), masses=[1, 1], D=2, and w_i=mass_i/D. Masses are nonnegative and sum exactly to D; uniform weights are not assumed. X=[0, 2] in index order and Y=[2, 0] 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(1, 1)

total mass numerator = 2

probability weight0 := div(1, 2)

probability weight0 = 1/2

probability weight1 := div(1, 2)

probability weight1 = 1/2

values=[0, 2];weights=[1/2, 1/2]

known finite probability law,not a sampled estimate

pointwise difference0 := sub(0, 2)

pointwise difference0 = -2

pointwise difference1 := sub(2, 0)

pointwise difference1 = 2

[-2, 2]

compute the variance of this shared-model difference

target variable weighted value0 := mul(1/2, -2)

target variable weighted value0 = -1

target variable weighted value1 := mul(1/2, 2)

target variable weighted value1 = 1

target variable mean := sum(-1, 1)

target variable mean = 0

centered difference0 := sub(-2, 0)

centered difference0 = -2

centered square0 := square(-2)

centered square0 = 4

centered contribution0 := mul(1/2, 4)

centered contribution0 = 2

centered difference1 := sub(2, 0)

centered difference1 = 2

centered square1 := square(2)

centered square1 = 4

centered contribution1 := mul(1/2, 4)

centered contribution1 = 2

[2/1, 2/1]

all indexed centered-square contributions retained

variance of the difference := sum(2, 2)

variance of the difference = 4

Reverse checks

• S018 · premise_and_result_audit — Recompute variance of the difference with exact rational arithmetic, not rounded decimals.
• S017 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.
• S016 · premise_and_result_audit — Recompute centered contribution1 with exact rational arithmetic, not rounded decimals.
• S015 · premise_and_result_audit — Recompute centered square1 with exact rational arithmetic, not rounded decimals.
• S014 · premise_and_result_audit — Recompute centered difference1 with exact rational arithmetic, not rounded decimals.
• S013 · premise_and_result_audit — Recompute centered contribution0 with exact rational arithmetic, not rounded decimals.
• S012 · premise_and_result_audit — Recompute centered square0 with exact rational arithmetic, not rounded decimals.
• S011 · premise_and_result_audit — Recompute centered difference0 with exact rational arithmetic, not rounded decimals.
• S010 · premise_and_result_audit — Recompute target variable mean with exact rational arithmetic, not rounded decimals.
• S009 · premise_and_result_audit — Recompute target variable weighted value1 with exact rational arithmetic, not rounded decimals.
• S008 · premise_and_result_audit — Recompute target variable weighted value0 with exact rational arithmetic, not rounded decimals.
• S007 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.
• S006 · premise_and_result_audit — Recompute pointwise difference1 with exact rational arithmetic, not rounded decimals.
• S005 · premise_and_result_audit — Recompute pointwise difference0 with exact rational arithmetic, not rounded decimals.
• S004 · premise_and_result_audit — Check against the original data and this step's premises; a one-way implication is not an equivalence.
• 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

4/1

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.