About 15% of people in a town have both a cat and a dog. As 64% of residents have a dog, what is the probability that someone in the town owns a cat, given they have a dog?
Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 53m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample2h 19m
- 10. Hypothesis Testing for Two Samples3h 22m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
4. Probability
Multiplication Rule: Dependent Events
Problem 3.2.24c
Textbook Question
"Using the Multiplication Rule In Exercises 19-32, use the Multiplication Rule.
24. Knowing a Person Who Was Murdered In a sample of 11,771 children ages 2 to 17, 8% have lost a friend or relative to murder. Four children are selected at random. (Adapted from University of New Hampshire)
c. Find the probability that at least one of the four has lost a friend or relative to murder."

1
Step 1: Understand the problem. We are tasked with finding the probability that at least one of the four randomly selected children has lost a friend or relative to murder. This is a complementary probability problem, where we first calculate the probability that none of the four children has lost a friend or relative to murder, and then subtract this value from 1.
Step 2: Define the probability of the complementary event. The probability that a single child has NOT lost a friend or relative to murder is 1 - 0.08 = 0.92 (since 8% of children have lost someone to murder).
Step 3: Use the Multiplication Rule to calculate the probability that none of the four children has lost a friend or relative to murder. Assuming the selections are independent, the probability that all four children have NOT lost someone is given by the product of their individual probabilities: \( P(\text{none}) = 0.92 \times 0.92 \times 0.92 \times 0.92 = 0.92^4 \).
Step 4: Calculate the probability of the event we are interested in (at least one child has lost a friend or relative to murder). This is the complement of the probability that none of the children has lost someone: \( P(\text{at least one}) = 1 - P(\text{none}) = 1 - 0.92^4 \).
Step 5: Conclude the solution. The final probability can be found by evaluating \( 1 - 0.92^4 \). This gives the probability that at least one of the four children has lost a friend or relative to murder.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Multiplication Rule
The Multiplication Rule in probability states that the probability of two independent events both occurring is the product of their individual probabilities. This rule is essential for calculating the likelihood of multiple events happening together, especially when dealing with random selections, as in this question.
Recommended video:
Multiplication Rule: Dependent Events
Complement Rule
The Complement Rule is a fundamental concept in probability that states the probability of an event occurring is equal to one minus the probability of it not occurring. In this context, to find the probability that at least one child has lost a friend or relative to murder, it is often easier to first calculate the probability that none have, and then subtract that from one.
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Conditional Probability Rule
Binomial Probability
Binomial Probability refers to the probability of obtaining a fixed number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. In this scenario, selecting four children can be modeled as a binomial experiment where 'success' is defined as a child having lost a friend or relative to murder, allowing for the application of binomial probability formulas.
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Calculating Probabilities in a Binomial Distribution
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