Problem 9
Question
\(A\) and \(B\) throw a dice. The probability that \(A\) 's throw is not greater than B's is (A) \(\frac{5}{12}\) (B) \(\frac{7}{12}\) (C) \(\frac{1}{6}\) (D) \(\frac{1}{2}\)
Step-by-Step Solution
Verified Answer
The probability is \(\frac{7}{12}\), which is option (B).
1Step 1: Understand the Problem
Both players, A and B, throw a single six-sided die. We are looking to find the probability that the result of A's throw is not greater than the result of B's throw.
2Step 2: Determine Sample Space
Each player can roll a die, resulting in one of 6 outcomes (1 through 6). Therefore, the total number of possible outcomes when both players throw their dice is \(6 \times 6 = 36\).
3Step 3: Identify Favorable Outcomes
A's throw is not greater than B's when either A equals B or A is less than B. Enumerate these outcomes:
- A = B: Possible with combinations (1,1), (2,2), (3,3), (4,4), (5,5), (6,6).
- A < B: For each value of A, count outcomes where B is greater.
- A=1: B=2,3,4,5,6 (5 outcomes)
- A=2: B=3,4,5,6 (4 outcomes)
- A=3: B=4,5,6 (3 outcomes)
- A=4: B=5,6 (2 outcomes)
- A=5: B=6 (1 outcome)
Total favorable outcomes are 6 + 5 + 4 + 3 + 2 + 1 = 21.
4Step 4: Calculate the Probability
The probability is the number of favorable outcomes divided by the total number of possible outcomes. \[P(A \leq B) = \frac{21}{36} = \frac{7}{12}\]
5Step 5: Verify if Answer Matches Given Options
The calculated probability \(\frac{7}{12}\) matches option B.
Key Concepts
Dice ProbabilitySample SpaceFavorable Outcomes
Dice Probability
When you roll a die, you're exploring the exciting world of probability. Probability simply refers to how likely an event is to happen. In the context of dice, it is about predicting the chances of rolling a particular number.
Each side of a six-sided die has an equal chance of landing face up.
This probability is \ \( \frac{1}{6} \ \), since there are six sides.
When both players throw a dice, we calculate the likelihood of different outcomes occurring by evaluating the probability of each specific event.
Having a good grasp of dice probability is crucial for games and other situations involving chance. It is essential to understand that each roll is independent of the others. This means the outcome of one roll does not affect another roll.
In our exercise, we use probability to determine how often Player A's dice roll is less than or equal to Player B's.
This involves calculating all possible outcomes and identifying which ones satisfy this condition.
Each side of a six-sided die has an equal chance of landing face up.
This probability is \ \( \frac{1}{6} \ \), since there are six sides.
When both players throw a dice, we calculate the likelihood of different outcomes occurring by evaluating the probability of each specific event.
Having a good grasp of dice probability is crucial for games and other situations involving chance. It is essential to understand that each roll is independent of the others. This means the outcome of one roll does not affect another roll.
In our exercise, we use probability to determine how often Player A's dice roll is less than or equal to Player B's.
This involves calculating all possible outcomes and identifying which ones satisfy this condition.
Sample Space
In probability, the concept of a sample space is pivotal.
The sample space of an experiment is the set of all possible outcomes. For dice, when you roll a single six-sided die, the sample space is \( \{1, 2, 3, 4, 5, 6\} \).
However, when both A and B roll their dice in the exercise, the scenario becomes a bit more complex.
The sample space for two dice rolls should consider every possible combination of outcomes from both dice.
The sample space of an experiment is the set of all possible outcomes. For dice, when you roll a single six-sided die, the sample space is \( \{1, 2, 3, 4, 5, 6\} \).
However, when both A and B roll their dice in the exercise, the scenario becomes a bit more complex.
The sample space for two dice rolls should consider every possible combination of outcomes from both dice.
- Think of it as a grid, with 6 possibilities for A and 6 possibilities for B, totaling 36 outcomes.
- Examples of these outcomes include \((1, 1), (1, 2), ..., (6, 6)\).
- This comprehensive view allows us to count how many possible interactions A's and B's dice rolls can have.
Favorable Outcomes
In probability exercises, once you have defined your sample space, the next step is to identify the favorable outcomes.
These are the outcomes that satisfy the condition of the problem statement. In our dice exercise, a favorable outcome occurs when Player A's roll is not greater than Player B's.
The exercise solution involved counting these specific outcomes.
Understanding how to count and use favorable outcomes is key in accurately determining probabilities in any dice game scenario.
These are the outcomes that satisfy the condition of the problem statement. In our dice exercise, a favorable outcome occurs when Player A's roll is not greater than Player B's.
The exercise solution involved counting these specific outcomes.
- For when A is equal to B, there are 6 combinations: \((1,1), (2,2), ..., (6,6)\).
- For A being less than B, the combinations include several sequences depending on the number A rolls.
- Combining all possible favorable scenarios results in 21 out of 36 unique outcomes.
Understanding how to count and use favorable outcomes is key in accurately determining probabilities in any dice game scenario.
Other exercises in this chapter
Problem 6
In an entrance test there are multiple choice questions. There are four possible answers to each question of which one is correct. The probability that a studen
View solution Problem 7
A person draws a card from a pack of 52 playing cards, replaces it and shuffles the pack. He continues doing this until be draws a spade, the chance that he wil
View solution Problem 10
A six faced die is so biased that it is twice likely to show an even number as compared to an odd number when thrown. The die is thorwn twice. The probability t
View solution Problem 11
\(n\) biscuits are distributed among \(N\) boys at random. The probability that particular boy gets \(r(
View solution