Problem Analysis #25

11.39s
3,140 toks
Problem Statement

Suppose the following conditions hold. A prize-drawing event uses a box containing 4 crimson balls and 5 blue balls. You are given four opportunities to draw a ball, without replacement.Under these conditions, you receive a prize of 100(10,000-won units) if you draw a crimson ball on the first draw, and 200(10,000-won units) if you draw a crimson ball on the fourth draw. Let XX be the random variable representing the total prize money obtained after drawing four balls from the box. If the expected value of XX is written aspq,\frac{p}{q},where pp and qq are relatively prime positive integers, find the value ofpq2.p \cdot q^2.oindent

Ground Truth
3600
Execution Trace
Reasoning Process

[THOUGHT] Compute the expected prize X. Since X = 100·I(first draw is crimson) + 200·I(fourth draw is crimson), by linearity of expectation we need P(first is crimson) and P(fourth is crimson). By symmetry in sampling without replacement, each draw position has the same probability of being crimson, namely 4/9. I will verify by enumerating all 4-draw sequences from the urn and computing the average payout. [/THOUGHT] [PYTHON] import itertools from fractions import Fraction

4 crimson (C), 5 blue (B); draw 4 without replacement (ordered)

balls = ['C']*4 + ['B']*5

total_prob = Fraction(0,1) EV = Fraction(0,1)

enumerate all ordered 4-tuples without replacement

for seq in itertools.permutations(range(9), 4): drawn = [balls[i] for i in seq] # probability of any specific ordered 4-draw sequence without replacement prob = Fraction(1, 987*6) total_prob += prob payout = 0 if drawn[0] == 'C': payout += 100 if drawn[3] == 'C': payout += 200 EV += prob * payout

total_prob, EV, float(EV) print(total_prob) print(EV) print(EV.numerator * EV.denominator**2) [/PYTHON][THOUGHT] The expected prize is (E[X]=100\Pr(\text{1st crimson})+200\Pr(\text{4th crimson})). By symmetry of drawing without replacement, each draw position has probability (4/9) of being crimson. Thus (E[X]=100\cdot\frac49+200\cdot\frac49=\frac{400}{3}). With (p=400,q=3), we need (p q^2=400\cdot 9=3600). [/THOUGHT] \boxed{3600}

Tool Output
[PYTHON OUTPUT] 1 400/3 3600 [/PYTHON OUTPUT]
Reasoning Process

[THOUGHT] From the Python output, (E[X]=\frac{400}{3}), so (p=400) and (q=3). Therefore (p\cdot q^2 = 400\cdot 3^2 = 3600). \boxed{3600}

Final Model Output
3600

Comparative Analysis (P25) (Average across runs)

Avg Time Taken

K-EXAONE-236B-A23B
164.4
Kanana-2-30B-Thinking
45.3
Gemini-3-Pro-Preview
35.8
Grok-4.1-fast
31.5
K-EXAONE-236B-A23B
28.9
HCX-007(high)
28.2
Deepseek-V3.2
27.9
Llama-VARCO-8B-Instruct
27.7
Solar-Pro-2 (31B)(high)
24.3
Kanana-2-30B-Thinking-2601
19.0
Solar-Open-100B
16.4
Claude-Opus-4.5
14.3
A.X-4.0 (72B)
13.5
GPT-5.1 (high)
13.4
GPT-5.2 (high)
11.4
axk1
5.7
EXAONE-4.0.1-32B (high)
3.9

Avg Token Usage

K-EXAONE-236B-A23B
18547.7
Kanana-2-30B-Thinking
9068.0
Kanana-2-30B-Thinking-2601
5758.5
Gemini-3-Pro-Preview
5595.0
Grok-4.1-fast
5445.0
Solar-Pro-2 (31B)(high)
5220.0
Solar-Open-100B
4781.0
K-EXAONE-236B-A23B
4410.0
HCX-007(high)
4007.0
Claude-Opus-4.5
3853.0
Deepseek-V3.2
3682.0
EXAONE-4.0.1-32B (high)
3480.0
GPT-5.2 (high)
3140.0
GPT-5.1 (high)
2933.0
axk1
2737.0
Llama-VARCO-8B-Instruct
1847.0
A.X-4.0 (72B)
1715.0