Problem 16
Question
A die is rolled twice. Find each probability. \(P(\text { two of the same number) }\)
Step-by-Step Solution
Verified Answer
The probability is \(\frac{1}{6}\).
1Step 1: Understand the Problem
We are asked to find the probability of rolling the same number on both rolls when a die is rolled twice. This means the outcome of the first roll must match the outcome of the second roll.
2Step 2: Determine Total Outcomes
A die has 6 sides, so there are 6 possible outcomes for each roll. When rolling a die twice, the total number of possible outcomes is the product of the outcomes for each roll, calculated as \(6 \times 6 = 36\).
3Step 3: Identify Favorable Outcomes
Two dice show the same number if both come up as 1, or both as 2, and so on until both show 6. Therefore, the favorable outcomes are \((1,1), (2,2), (3,3), (4,4), (5,5), (6,6)\), making a total of 6 favorable outcomes.
4Step 4: Calculate Probability
The probability of rolling the same number on both dice is the number of favorable outcomes divided by the total number of possible outcomes. Hence, the probability \(P\) is calculated as \(P = \frac{6}{36} = \frac{1}{6}\).
Key Concepts
Sample SpaceFavorable OutcomesTotal Outcomes
Sample Space
When engaging in probability problems, understanding the concept of a sample space is fundamental. A **sample space** is the set of all possible outcomes of a probabilistic experiment. In this case, the experiment consists of rolling a die twice. Each roll results in one of six possible outcomes, ranging from 1 to 6.
For multiple independent events, such as rolling a die twice, the sample space is the Cartesian product of the individual sample spaces for each event. Thus, the total sample space for rolling a die twice is represented by all possible pairs: (1,1), (1,2), ..., (6,6). There are 36 such pairs, as each first roll can be paired with each outcome of the second roll. Recognizing the sample space helps us establish a foundation to further determine specific outcomes and probabilities.
For multiple independent events, such as rolling a die twice, the sample space is the Cartesian product of the individual sample spaces for each event. Thus, the total sample space for rolling a die twice is represented by all possible pairs: (1,1), (1,2), ..., (6,6). There are 36 such pairs, as each first roll can be paired with each outcome of the second roll. Recognizing the sample space helps us establish a foundation to further determine specific outcomes and probabilities.
Favorable Outcomes
In any probability question, identifying the **favorable outcomes** is crucial. These are the outcomes that fulfill the conditions of the event we are focusing on.
For the problem at hand, we are interested in the scenario where both dice show the same number. Thus, favorable outcomes are pairs where the numbers are identical, such as (1,1), (2,2), ..., (6,6).
For the problem at hand, we are interested in the scenario where both dice show the same number. Thus, favorable outcomes are pairs where the numbers are identical, such as (1,1), (2,2), ..., (6,6).
- (1,1)
- (2,2)
- (3,3)
- (4,4)
- (5,5)
- (6,6)
Total Outcomes
Calculating probability requires knowing both the favorable outcomes and the **total outcomes**. The total outcomes give the complete picture of possibilities for an event to happen.
In our case, when rolling a die twice, each roll has 6 possible outcomes. Since these events are independent (the result of the first roll doesn't affect the second), the total number of outcomes is the product of the possibilities for each roll. Hence, we have:
This number serves as the denominator in our probability fraction. By dividing the number of favorable outcomes by this total, we determine the probability of the event occurring.
In our case, when rolling a die twice, each roll has 6 possible outcomes. Since these events are independent (the result of the first roll doesn't affect the second), the total number of outcomes is the product of the possibilities for each roll. Hence, we have:
- First roll: 6 possible outcomes
- Second roll: 6 possible outcomes
This number serves as the denominator in our probability fraction. By dividing the number of favorable outcomes by this total, we determine the probability of the event occurring.
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