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Consider a family with a mother, father, and two children. Let \(A_{1}=\left\\{\text { mother has influenzal, } A_{2}=\\{ \text { father has influenzal, }\right.\) \(A_{3}=\left\\{\text { first child has influenzal, } A_{4}=\\{ \text { second child has influ- }\right.\) enzal, \(B=\) lat least one child has influenzal, \(C=\) lat least one parent has influenzal, and \(D=\\{\) at least one person in the family has influenzal.Express \(D\) in terms of \(B\) and \(C .\)

Short Answer

Expert verified
\(D = B \cup C\)

Step by step solution

01

Understand the problem and express D

The problem involves expressing the event "at least one person in the family has influenza" using the events "at least one child has influenza" and "at least one parent has influenza." This requires understanding that if either at least one child or at least one parent has influenza, then someone in the family has influenza.
02

Use set operations for expression

To express the event \( D \) in terms of \( B \) and \( C \), we use the union of these two events. In set theory, when we say at least one of several events occurs, we are referring to the union of these events. Therefore, \( D = B \cup C \).
03

Interpret the solution

The union \( B \cup C \) represents the occurrence that at least one event between children having influenza and parents having influenza is true, thereby covering all cases where anyone in the family has influenza. This satisfies the condition for \( D \).

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Probability Events
Probability events are fundamental to understanding biostatistics and many other fields that rely on statistical analysis. In this family-related problem, we're looking at specific events defined by who in the family might have influenza.
Each event is a statement about a particular subset of the family, such as "the mother has influenza" or "at least one child has influenza." These events have probabilities associated with how likely they are to occur.
  • Single Event: For example, the event that the mother has influenza, denoted by \(A_1\), is an individual probability event.
  • Compound Event: When considering "at least one child has influenza" (B) or "at least one parent has influenza" (C), we are dealing with compound probability events. These involve multiple scenarios adding together to fulfill the condition.
Understanding how these events relate helps us utilize probability theory to compute the likelihood of various health outcomes within the family.
Union of Sets
The union of sets in set theory helps describe situations where multiple events can occur. In our exercise, we must express the scenario "at least one person in the family has influenza" in terms of other defined events.
This involves the union of the set representing children with influenza (B) and parents with influenza (C). The union, represented by \(B \cup C\), means that if either event B or C happens, it's enough to meet the condition of our set D.
  • Union Operation: The operation is critical here. Set union incorporates all elements from both sets, providing a thorough understanding of all possible outcomes.
  • Set Representation: When using the union, imagine overlapping circles in a Venn diagram. The union includes every area that any circle covers.
This makes the set union a powerful way to simplify complex probability events like the ones dealing with family health statistics.
Family Health Statistics
Family health statistics often require us to consider various aspects of probability and set theory. By examining a family's health based on whether members have influenza, we apply these statistical methods to understand the bigger picture.
This particular exercise reflects real-life scenarios where multiple factors interact, showing how comprehensive health data is analyzed.
  • Analyzing Trends: When collecting family health statistics, it's important to determine how individual health events (like having the flu) impact overall family health.
  • Interpreting Data: Understanding relationships between events, like our events B and C, helps us spot trends and correlations that might suggest larger health patterns.
  • Preventive Measures: By analyzing these statistics, healthcare services can tailor preventive measures, optimize resource allocation, and make better health predictions for families.
Understanding family health statistics through probability and the union of sets equips us with tools to analyze complex medical data effectively, leading to improved healthcare decisions.

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Most popular questions from this chapter

Consider a family with a mother, father, and two children. Let \(A_{1}=\left\\{\text { mother has influenzal, } A_{2}=\\{ \text { father has influenzal, }\right.\) \(A_{3}=\left\\{\text { first child has influenzal, } A_{4}=\\{ \text { second child has influ- }\right.\) enzal, \(B=\) lat least one child has influenzal, \(C=\) lat least one parent has influenzal, and \(D=\\{\) at least one person in the family has influenzal.Express \(C\) in terms of \(A_{1}, A_{2}, A_{3},\) and \(A_{4}\).

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