Two people, A and B, each have a bag containing three cards with the numbers 1, 2, and 3 written on them. They simultaneously draw one card from their bag and compare the numbers. If the numbers are the same, it's a draw. If the numbers are different, the person with the larger number wins. (1) Find the probability of a draw in one round. (2) If this game is played 4 times, with the drawn card being returned to the bag each time, find: (i) The probability that A wins at least 3 times. (ii) The probability that A wins once, loses once, and there are two draws. (iii) The probability that A's number of wins equals B's number of wins, and the probability that A's number of wins is greater than B's number of wins.

Probability and StatisticsProbabilityBinomial DistributionCombinatoricsProbability of Events
2025/3/31

1. Problem Description

Two people, A and B, each have a bag containing three cards with the numbers 1, 2, and 3 written on them. They simultaneously draw one card from their bag and compare the numbers. If the numbers are the same, it's a draw. If the numbers are different, the person with the larger number wins.
(1) Find the probability of a draw in one round.
(2) If this game is played 4 times, with the drawn card being returned to the bag each time, find:
(i) The probability that A wins at least 3 times.
(ii) The probability that A wins once, loses once, and there are two draws.
(iii) The probability that A's number of wins equals B's number of wins, and the probability that A's number of wins is greater than B's number of wins.

2. Solution Steps

(1) The possible outcomes of a single round are: (1,1), (1,2), (1,3), (2,1), (2,2), (2,3), (3,1), (3,2), (3,3). There are a total of 3×3=93 \times 3 = 9 possible outcomes. The draws are (1,1), (2,2), (3,3). Therefore, the number of draws is

3. The probability of a draw is $\frac{3}{9} = \frac{1}{3}$.

L=1L = 1 and M=3M = 3.
(2)
In a single round, let the probability of A winning be pp, the probability of A losing be qq, and the probability of a draw be rr.
Since the game is symmetric, p=qp = q. We also know that p+q+r=1p + q + r = 1.
We found r=13r = \frac{1}{3}, so p+q=23p + q = \frac{2}{3}. Since p=qp = q, we have 2p=232p = \frac{2}{3}, which means p=13p = \frac{1}{3} and q=13q = \frac{1}{3}.
(i) We want to find the probability that A wins at least 3 times in 4 rounds. This means A can win 3 times or 4 times.
The probability of A winning exactly 3 times is given by the binomial probability formula:
P(A=3)=(43)p3(1p)43=(43)(13)3(23)1=4×127×23=881P(A=3) = \binom{4}{3} p^3 (1-p)^{4-3} = \binom{4}{3} (\frac{1}{3})^3 (\frac{2}{3})^1 = 4 \times \frac{1}{27} \times \frac{2}{3} = \frac{8}{81}
The probability of A winning exactly 4 times is:
P(A=4)=(44)p4(1p)44=(44)(13)4(23)0=1×181×1=181P(A=4) = \binom{4}{4} p^4 (1-p)^{4-4} = \binom{4}{4} (\frac{1}{3})^4 (\frac{2}{3})^0 = 1 \times \frac{1}{81} \times 1 = \frac{1}{81}
So the probability of A winning at least 3 times is:
P(A3)=P(A=3)+P(A=4)=881+181=981=19P(A \ge 3) = P(A=3) + P(A=4) = \frac{8}{81} + \frac{1}{81} = \frac{9}{81} = \frac{1}{9}
N=1N = 1 and O=9O = 9.
(ii) We want to find the probability that A wins once, loses once, and there are two draws.
The number of ways to arrange 1 win, 1 loss, and 2 draws is given by 4!1!1!2!=242=12\frac{4!}{1!1!2!} = \frac{24}{2} = 12.
The probability of each arrangement is p1q1r2=(13)1(13)1(13)2=(13)4=181p^1 q^1 r^2 = (\frac{1}{3})^1 (\frac{1}{3})^1 (\frac{1}{3})^2 = (\frac{1}{3})^4 = \frac{1}{81}.
Therefore, the probability of A winning once, losing once, and having two draws is:
12×181=1281=42712 \times \frac{1}{81} = \frac{12}{81} = \frac{4}{27}.
P=4P = 4, Q=2Q = 2, and R=7R = 7. Thus the probability is 427\frac{4}{27}.
(iii) A's number of wins equals B's number of wins. Since there are 4 rounds, this means A and B both win 0, 1, or 2 times.
Case 1: A and B both win 0 times. This means all 4 rounds are draws. The probability is r4=(13)4=181r^4 = (\frac{1}{3})^4 = \frac{1}{81}.
Case 2: A and B both win 1 time. This means there are 2 draws. The number of arrangements is 4!1!1!2!=12\frac{4!}{1!1!2!} = 12. The probability is 12×(13)1(13)1(13)2=12×181=128112 \times (\frac{1}{3})^1 (\frac{1}{3})^1 (\frac{1}{3})^2 = 12 \times \frac{1}{81} = \frac{12}{81}.
Case 3: A and B both win 2 times. This means there are 0 draws. The number of arrangements is 4!2!2!=6\frac{4!}{2!2!} = 6. The probability is 6×(13)2(13)2=6×181=6816 \times (\frac{1}{3})^2 (\frac{1}{3})^2 = 6 \times \frac{1}{81} = \frac{6}{81}.
The total probability is 181+1281+681=1981\frac{1}{81} + \frac{12}{81} + \frac{6}{81} = \frac{19}{81}.
Therefore, ST=19ST = 19 and UV=81UV = 81.
Since the only possibilities are A wins more than B, B wins more than A, or A and B win the same number of times, and the probabilities of A winning more and B winning more are the same, we have
P(A>B)+P(B>A)+P(A=B)=1P(A > B) + P(B > A) + P(A = B) = 1.
P(A>B)=P(B>A)P(A > B) = P(B > A).
2P(A>B)+P(A=B)=12 P(A > B) + P(A = B) = 1.
2P(A>B)=11981=62812 P(A > B) = 1 - \frac{19}{81} = \frac{62}{81}.
P(A>B)=3181P(A > B) = \frac{31}{81}.
Therefore, WX=31WX = 31.

3. Final Answer

L/M = 1/3
N/O = 1/9
P/QR = 4/27
ST/UV = 19/81
WX/UV = 31/81

Related problems in "Probability and Statistics"

The problem provides a frequency distribution table of marks obtained by students. Part (a) requires...

ProbabilityConditional ProbabilityWithout ReplacementCombinations
2025/6/5

The problem is divided into two questions, question 10 and question 11. Question 10 is about the fre...

Frequency DistributionCumulative FrequencyOgivePercentileProbabilityConditional ProbabilityCombinations
2025/6/5

A number is selected at random from the integers 30 to 48 inclusive. We want to find the probability...

ProbabilityPrime NumbersDivisibility
2025/6/3

The problem describes a survey where 30 people answered about their favorite book genres. The result...

PercentagesData InterpretationPie ChartFractions
2025/6/1

The problem asks us to determine if there is a statistically significant difference in promotion rat...

Hypothesis TestingChi-Square TestContingency TableStatistical SignificanceIndependence
2025/6/1

We are given a contingency table showing the number of students from different majors (Psychology, B...

Chi-Square TestContingency TableStatistical InferenceHypothesis Testing
2025/6/1

The problem describes a scenario where a pizza company wants to determine if the number of different...

Chi-Square TestGoodness-of-Fit TestHypothesis TestingFrequency DistributionP-value
2025/6/1

The problem asks to test the significance of three chi-square tests given the sample size $N$, numbe...

Chi-square testStatistical SignificanceDegrees of FreedomEffect SizeCramer's VHypothesis Testing
2025/5/29

The problem asks us to compute the expected frequencies for the given contingency table. The conting...

Contingency TableExpected FrequenciesChi-squared Test
2025/5/29

The problem asks us to estimate the chi-square value when $n=23$ and $p=99$, given a table of chi-sq...

Chi-square distributionStatistical estimationInterpolation
2025/5/27