Conditional Probability — Practice Quiz
A Probability cheat sheet for Conditional Probability — every key formula with its symbols defined — plus a medium-level practice quiz to test recall.
Formulas & key concepts
Conditional Probability
Where: \(P(B) \neq 0\)
Bayes' Theorem
Law of Total Probability
Where: \(B_i\) partition the sample space
Practice quiz
If $P(A \cap B) = 0.2$ and $P(B) = 0.5$, what is $P(A|B)$?
- $0.1$
- $0.4$
- $0.25$
- $0.7$
Answer: $0.4$
Given $P(B_1) = 0.3$, $P(B_2) = 0.7$, $P(A|B_1) = 0.6$, and $P(A|B_2) = 0.2$, where $B_1$ and $B_2$ form a partition of the sample space. What is $P(A)$?
- $0.8$
- $0.24$
- $0.32$
- $0.42$
Answer: $0.32$
If $P(A|B) = 0.7$, $P(B) = 0.4$, and $P(A) = 0.5$, what is $P(B|A)$?
- $0.28$
- $0.56$
- $0.35$
- $0.8$
Answer: $0.56$
For two events $A$ and $B$, if $P(A|B) = P(A)$, what can be concluded about $A$ and $B$?
- $A$ and $B$ are mutually exclusive
- $A$ and $B$ are independent
- $A$ is a subset of $B$
- $B$ is a subset of $A$
Answer: $A$ and $B$ are independent
The Law of Total Probability requires that the events $B_i$ form a partition of the sample space. Which of the following conditions is NOT necessarily true for a partition?
- The events $B_i$ are mutually exclusive
- The union of all $B_i$ covers the entire sample space
- $P(B_i) > 0$ for all $i$
- The events $B_i$ are independent
Answer: The events $B_i$ are independent
A factory produces items using two machines, $M_1$ and $M_2$. $M_1$ produces $60\%$ of the items and $M_2$ produces $40\%$. $2\%$ of items from $M_1$ are defective, and $3\%$ of items from $M_2$ are defective. If an item is found to be defective, what is the probability it came from $M_1$?
- $0.6$
- $0.5$
- $0.024$
- $0.4$
Answer: $0.5$
Which of the following expressions is equivalent to $P(A \cap B)$?
- $P(A|B)P(A)$
- $P(B|A)P(B)$
- $P(A|B)P(B)$
- $P(A) + P(B)$
Answer: $P(A|B)P(B)$
Bayes' Theorem is primarily used to calculate:
- The probability of the intersection of two events
- The probability of the union of two events
- The posterior probability of an event given new evidence
- The marginal probability of an event
Answer: The posterior probability of an event given new evidence
Suppose there are three disjoint and exhaustive events $B_1, B_2, B_3$ such that $P(B_1) = 0.2$, $P(B_2) = 0.5$, $P(B_3) = 0.3$. If $P(A|B_1) = 0.1$, $P(A|B_2) = 0.4$, and $P(A|B_3) = 0.3$, what is $P(A)$?
- $0.8$
- $0.31$
- $0.25$
- $0.4$
Answer: $0.31$
In a certain population, $10\%$ of people have a specific genetic marker ($M$). A test for this marker is $95\%$ accurate for those who have the marker (true positive rate) and $90\%$ accurate for those who do not have the marker (true negative rate). If a person tests positive for the marker, what is the probability they actually have the marker?
- $0.95$
- $0.185$
- $0.5135$
- $0.095$
Answer: $0.5135$
Select a subject
Select a subject from the left panel to begin exploring formulas.