Conditional Probability
Use “given” to identify the group you are studying. Learn to choose the right denominator, distinguish conditional from joint probability, and multiply probabilities correctly when a process has several steps.
By the end of this lesson, you should be able to:
- Read as “the probability of given .”
- Restrict the sample space to the event after the vertical bar.
- Calculate conditional probabilities from outcome lists, tables and given probabilities.
- Explain why reversing the condition can change the answer.
- Use the general multiplication rule, including draws without replacement.
Before you start: Be comfortable identifying an intersection and calculating a joint probability. Review Topic 2.5: Mutually Exclusive Events if needed.
First time learning this? Follow the example. Keep asking, “Among which outcomes am I counting?”
Here to revise? Use the denominator checklist, then try the practice before opening the solutions.
The concept in 60 seconds
Conditional probability is the chance of an event within a specified group. The word “given” tells you which outcomes remain eligible.
Suppose ticket is drawn uniformly from numbers . You are told that its number is at least . Only , and remain possible under that information. To find the chance of an even number, count even results among those eligible results.
Ask “among which group?”
Among tickets numbered at least , numbers are even. The conditional probability is .
equally likely possibilities after using the information.
“Outside ” numbers do not enter this conditional denominator. Dark tickets satisfy both and the even target; text labels identify the groups as well as color.
The original bag still has tickets. The information changes the group used in the calculation; it does not physically remove tickets.
Quick check: why is the denominator instead of ?
We are calculating the chance of even given that the number is at least . The eligible outcomes are , and . The denominator must describe that given group.
The ticket question
A bag contains identical, well-mixed tickets numbered , . ticket is drawn without looking. All numbered tickets are equally likely.
- : the number is even, so .
- : the number is at least , so .
- : both conditions hold, so .
Question: Given that the drawn number is at least , what is the probability that it is even?
The target is , and the given event is . We therefore want . The eligible group is ; within it, the successful outcomes are the shared outcomes .
Knowing does not make all tickets eligible for this calculation, and it does not tell us that must occur: ticket is still possible.
Key ideas and notation
Target event:
The event whose chance we want.
In , is on the left of the bar.
Given event:
The information that restricts the eligible group.
In , is on the right of the bar.
Intersection:
The outcomes satisfying both the target and the condition.
Tickets and are both even and at least .
Conditional probability
The share of the given group that also satisfies the target.
for the ticket question.
Provided .
Read the bar as “given,” not as division. The fraction on the right shows how to calculate the probability.
For equally likely individual outcomes, the whole-space denominator cancels:
Ticket example: .
Given group: all tickets
Target count:
Given group: all tickets
Shared count:
Given group: tickets in
Shared count:
: even; : at least . Joint and conditional probabilities use the same shared outcomes, but they describe different eligible groups.
If the outcomes have unequal probabilities, use their probability weights in the formula. Counting labels alone can give the wrong answer.
Read a conditional probability from a two-way table
Use the same original -student teaching table as in Topic 2.5. A student can belong to both Chess and Music. listed students is selected uniformly at random.
Let mean “Chess member” and mean “Music member.” The table shows how these two memberships overlap.
| Chess member? | Music Yes | Music No | Row total |
|---|---|---|---|
| Yes | |||
| No | |||
| Total |
Shared count:
Chess total:
Shared count:
Music total:
: Chess member; : Music member. This is an original fictional teaching table. All probabilities refer to from the listed students.
Given Chess: use the Chess row
There are Chess members, and of them are also Music members. Thus .
Given Music: use the Music column
There are Music members, and of them are also Chess members. Thus .
The shared numerator is in both calculations, but the given groups differ. That is why and need not be equal. By contrast, the joint probability is .
A reliable table routine: circle the word after “given,” find that row or column total, then divide the shared cell by that total.
Keep the condition fixed
Complements within the given group
Among Chess members, a student either belongs to Music or does not. These two possibilities cover the same -student given group.
Eligible group: all Chess members
The bar divides the same given group into target and target complement. Its segment widths are and . The condition stays Chess in both probabilities.
, provided .
The complement changes the target on the left, while the condition stays fixed. asks about a different given group and cannot generally be found by subtracting from .
A zero-probability condition
The ratio formula requires . If , division by is undefined. In the finite ticket model, “given the number is ” is not an eligible condition because no ticket exists.
A conditional probability of is possible when the given group has positive probability but contains no target outcomes. For example, on a fair die, because the contain no odd number.
Information does not establish a cause
A conditional percentage describes a group. Saying that of Chess members belong to Music does not show that Chess membership caused Music membership.
Use the general multiplication rule
Rearranging the conditional probability formula gives the chance that both events occur:
.
Equivalently, .
The factor after the multiplication sign must use the first factor’s event as its condition. That conditioning event must have positive probability. In the club example, .
This is the general rule. It does not require the events to be independent. Do not replace with unless the event relationship justifies it.
Draws without replacement: update what remains
A bag contains Green tokens and Gold tokens, identical in size and thoroughly mixed. tokens are drawn sequentially without replacement; each remaining token is equally likely at each draw. complete trial consists of both draws.
Second Green given first Green:
Second Gold given first Green:
Second Green given first Gold:
Second Gold given first Gold:
Each chip represents token. Labels distinguish Green and Gold; both counts and the remaining total matter for the second-draw probabilities.
Let mean “first token is Green” and mean “second token is Green.” After a first Green token, Green tokens remain among tokens, so .
.
Ordered path:
Ordered path:
Ordered path:
Ordered path:
Each second-draw probability is conditional on the first-draw result. Multiply along a path to find its joint probability. The complete path probabilities total .
Read a path from its first result to its second result, then multiply along that path. Second-draw probabilities are conditional on the first result.
With replacement and thorough mixing between draws, the bag would return to Green and Gold tokens. Then the Green–Green probability would be . Replacement changes the model, so name it before calculating.
Worked examples
Example 1: restrict an outcome list
Question: ticket is drawn uniformly from numbers . Given that its number is at least , what is the probability that it is even?
- Given group .
- Target outcomes within are .
- .
Interpretation: among the eligible numbers at least , . The answer is about , rather than the joint probability .
Example 2: reverse the condition carefully
Question: Use the -student club table to compare and .
- Given Chess, the eligible group has students: .
- Given Music, the eligible group has students: .
Check: both use the shared count . Reversing the bar changes the denominator, so the answers differ.
Example 3: divide given probabilities
Question: A fictional course model gives and . Find .
- The condition is Attend, so its probability is the denominator.
- .
Interpretation: within the Attend event, the model’s pass probability is . The joint probability describes both events within the whole model.
Example 4: multiply using the stated condition
Question: A workshop model gives and . Find the probability of registering and bringing a laptop.
- The target is the joint event .
- Use .
- The joint probability is .
Interpretation: the model gives a chance of both events. The value is a conditional probability; it is not automatically the overall probability of bringing a laptop.
Example 5: without replacement
Question: tokens are drawn without replacement from the bag with Green and Gold tokens. Find the probability that both are Green.
- First Green probability: .
- After a first Green, the remaining bag contains Green and Gold tokens.
- Second Green given first Green: .
- .
Check: the second numerator and denominator both change. Using again would ignore the removal of the first token.
Example 6: a conditional complement
Question: Given that the selected student belongs to Chess, what is the probability that the student does not belong to Music?
- The condition remains Chess, with eligible students.
- There are Chess members who are not in Music.
- .
Alternative: . Subtracting the joint probability from would answer a different question.
Explain in context
Start your interpretation with “Among…” or “Given that…”. That makes the denominator visible in your words as well as in your calculation.
A complete table response: “Given that the selected student is a Chess member, the eligible group contains students. belong to Music, so . Among Chess members in this listed group, are Music members.”
A good multiplication response identifies the first event probability and the appropriate conditional probability, then interprets their product as the chance that both events occur.
Improve this answer: “The Music probability is .”
The statement omits its condition. A clearer answer is: “The probability of Music membership given Chess membership is .” Overall Music membership in this table has probability , so the two statements describe different groups.
Before finishing: check the direction of the bar, identify the given group, show the ratio or conditional product, and keep the condition in the interpretation.
Find and fix mistakes
| Mistake | Better reasoning |
|---|---|
| Use the whole table total for every probability. | For , use the Chess members, not all students. |
| Reverse and . | Read the right side of the bar first. It determines the denominator. |
| Use in the conditional formula. | Use the shared numerator , not the target probability alone. |
| Treat the bar as a multiplication or division symbol. | The bar means “given.” Translate the target and condition before choosing a calculation. |
| Replace the second conditional factor by an overall probability automatically. | Use . Only simplify further when the event relationship allows it. |
| Keep both draw probabilities unchanged without replacement. | Update the remaining target count and total after the first draw. |
| Complement the condition when using minus. | keeps fixed. is a different question. |
| Say that a conditioning probability gives conditional probability . | Division by is undefined. The basic ratio requires a positive given-event probability. |
| Accept a conditional probability above . | Check the data and denominator: a shared group cannot be larger than the given group. |
| Omit the given group from the interpretation. | State “Among Chess members, belong to Music,” rather than calling the overall Music probability. |
Fast reasonableness checks: a conditional probability must lie from to . The joint numerator probability cannot exceed the given event probability. If a conditional ratio exceeds , inspect the event definitions, numerator and denominator.
Practice with hints and solutions
Underline the condition first. Write the eligible group or its total before doing any arithmetic.
1. Even given
ticket is drawn uniformly from numbers . Write the eligible outcomes and calculate .
Hint for question 1
The condition keeps only , and . Which of those are even?
Solution for question 1
The eligible outcomes are ; the target outcomes within that group are . The conditional probability is .
2. Reverse the ticket question
For the same draw, calculate . Explain why its denominator differs from question 1.
Hint for question 2
The event after the bar is now even. List all .
Solution for question 2
The given group is . The numbers at least within it are , so the probability is . The shared outcomes are unchanged, but the condition changes the eligible group from outcomes .
3. given even
A fair die is . Given that its result is even, what is the probability that it is greater than ?
Hint for question 3
Restrict to . “Greater than ” does not include .
Solution for question 3
Only meets the target among the . . The whole-space joint probability would instead be .
4. Not Chess given Music
Use the -student club table. listed student is selected uniformly. Find .
Hint for question 4
The given group is the Music Yes column, with students.
Solution for question 4
Music members are not in Chess. The probability is . This also equals .
5. Use the conditional formula
A model gives and . Find .
Hint for question 5
Divide the joint probability by the probability of the event after the bar.
Solution for question 5
. The condition has positive probability, and the joint probability is no greater than .
6. From conditional to joint
A fictional school model gives and . Find the probability of being late and forgetting a notebook.
Hint for question 6
Use the general multiplication rule with Late as the first event.
Solution for question 6
. The second factor is conditional on Late; the answer is the chance that both events occur.
7. without replacement
Use the bag with Green and Gold tokens. Given that the first token is Gold, find the probability that the second is Gold. Then find the probability that both are Gold.
Hint for question 7
After a first Gold token, Gold token remains among tokens.
Solution for question 7
. . The conditional probability and the joint probability answer different questions.
8. Green then Gold
tokens are drawn without replacement from the same bag. Find the probability that the first is Green and the second is Gold.
Hint for question 8
After a first Green, both Gold tokens are still in the bag.
Solution for question 8
, and . The joint probability is .
9. Complement the target, not the condition
Let mean “completes the task” and mean “uses the online version.” Given , find . Does the same information determine ?
Hint for question 9
Keep fixed for the complement calculation. Not is a different given group.
Solution for question 9
. The information does not determine , because that asks about users of a different version.
10. Check whether the formula can be used
Consider two separate cases: (i) and ; (ii) a proposed model reports and . Can either case give a valid value of using the ratio formula?
Hint for question 10
Check for division by , then check whether the joint group can be larger than the given group.
Solution for question 10
(i) Undefined: the ratio is , not . The condition fails. (ii) Invalid proposed model: the joint probability cannot exceed . The ratio flags incompatible inputs; it is not a valid conditional probability.
Quick revision
Questions students often ask
Does “given” always mean an earlier event in time?
No. A condition is information used to identify the eligible group. Club membership can be a condition even though the two memberships are recorded at the same time. In sequential draws, an earlier result can also supply the condition.
Does conditioning always change the numerical probability?
No. Conditioning restricts the eligible group to the given event; its target share may equal the overall target share. Use the calculation rather than assuming the value must increase or decrease.
Must I assume independence to use the general multiplication rule?
No. The general rule already uses the appropriate conditional probability. Independence is needed to replace that conditional probability with an unconditional one; that relationship is studied in Topic 2.7.
Can be larger than ?
Yes. For , dividing the joint probability by can increase its value because is at most . In the club table, while .
Final understanding check
A new original teaching example lists students and their Art and Science club memberships. listed student is selected uniformly at random. means “Art member,” and means “Science member.”
| Art member? | Science Yes | Science No | Row total |
|---|---|---|---|
| Yes | |||
| No | |||
| Total |
- Find .
- Find and interpret it in words.
- Find . Explain why it differs from .
- Find using the same given group.
- Find . Explain why this is not .
- Use to recover the joint probability.
- In a separate draw from the bag without replacement, calculate .
Open the complete final-check solution
- .
- . Among Science members in this group, also belong to Art.
- . It uses the Art members as its given group, rather than the Science members.
- , also .
- . The given group is the non-Science members, so it is a different condition.
- .
- First Gold has probability . After a first Gold, Green tokens remain among tokens. The joint probability is .
Ready to move on? You should be able to name the given group, choose its denominator, reverse a condition carefully, and use a conditional probability in a product. If you used for every table question, review the given-group totals before continuing.
Continue learning
Check when knowing one event does not change another event’s probability. Then calculate probabilities for “ or ,” including their shared outcomes.
← Topic 2.5: Mutually Exclusive Events
Review conditional table probabilities · Review the multiplication rule · Back to the lesson overview