Dependent and Independent Events
You flip a coin and then roll a die: what shows up on the coin changes nothing about what the die can show. But if you draw a card from a deck and don't put it back, the second card comes from a different deck. How do we tell one case from the other with numbers? That is the question of this page, and the answer is the foundation of almost every multi-stage probability calculation.
Independent events
Why the formula? Because $P(A \cap B) = P(A)\,P(B|A)$ always holds; if $B$ does not depend on $A$, then $P(B|A) = P(B)$ and the product is what remains.
In a random experiment, a fair coin (with sides $C$ and $X$) and a six-sided die numbered 1 to 6 are rolled. Consider the following events: $A$: "Getting heads on the…
In a random experiment, a fair coin (with sides $C$ and $X$) and a six-sided die numbered 1 to 6 are rolled. Consider the following events:
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$A$: "Getting heads on the coin".
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$B$: "Getting an even number on the die".
Reason whether the events $A$ and $B$ are dependent or independent, and calculate the probability that both occur at the same time, that is, $P(A \cap B)$.
A basketball player has a probability of $0.8$ of making a free throw. If they shoot two free throws in a row and we assume that success in the second shot is…
A basketball player has a probability of $0.8$ of making a free throw. If they shoot two free throws in a row and we assume that success in the second shot is independent of the outcome of the first, calculate:
- a) The probability that they make both shots.
- b) The probability that they miss both shots.
- c) The probability that they make at least one shot.
In a 2nd Baccalaureate class, $40\%$ of students regularly use the social network Instagram ($I$) and $25\%$ use TikTok ($T$). It is also known that the use of both…
In a 2nd Baccalaureate class, $40\%$ of students regularly use the social network Instagram ($I$) and $25\%$ use TikTok ($T$). It is also known that the use of both networks is independent of each other. If we choose a student at random, calculate the probability that:
- a) They use both social networks.
- b) They use neither of them.
Draws: with and without replacement
An urn contains 5 orange balls and 3 purple balls. Two balls are drawn one after the other with replacement (the first ball is returned to the urn before the second one…
An urn contains 5 orange balls and 3 purple balls. Two balls are drawn one after the other with replacement (the first ball is returned to the urn before the second one is drawn).
- a) Calculate the probability that both balls drawn are orange.
- b) Does the result of the first draw affect the probability of the second? Justify your answer.
Using the same urn as in the previous exercise (5 orange and 3 purple balls), two balls are now drawn without replacement. a) Calculate the probability that the second…
Using the same urn as in the previous exercise (5 orange and 3 purple balls), two balls are now drawn without replacement.
- a) Calculate the probability that the second ball is orange given that the first was purple.
- b) Are these events independent? Justify your answer by comparing this result with the probability of drawing an orange ball on the first draw.
In a pencil case there are 10 felt-tip pens: 6 are blue and 4 are red. Two felt-tip pens are drawn successively without replacement. a) What is the probability that both…
In a pencil case there are 10 felt-tip pens: 6 are blue and 4 are red. Two felt-tip pens are drawn successively without replacement.
- a) What is the probability that both are blue?
- b) What is the probability that the second is red given that the first was blue?
- c) Are the events "the first felt-tip pen is blue" and "the second felt-tip pen is blue" independent? Justify your answer by comparing the conditional probabilities.
Checking whether two events are independent
Another way to check is with conditional probabilities: if $P(B|A) = P(B|A^c)$, the outcome of $A$ does not change $B$. If they are different, there is dependence.
Let $A$ and $B$ be two events in a sample space such that their probabilities are known: $P(A) = 0.6$ and $P(B) = 0.4$. If we know that the events are independent,…
Let $A$ and $B$ be two events in a sample space such that their probabilities are known: $P(A) = 0.6$ and $P(B) = 0.4$. If we know that the events are independent, calculate:
- a) $P(A \cap B)$
- b) $P(A \cup B)$
- c) $P(A|B)$
The following information is available about two events $X$ and $Y$: $P(X) = 0.5$, $P(Y) = 0.3$ and $P(X \cap Y) = 0.15$. Prove mathematically whether the events $X$ and…
The following information is available about two events $X$ and $Y$:
$P(X) = 0.5$, $P(Y) = 0.3$ and $P(X \cap Y) = 0.15$.
Prove mathematically whether the events $X$ and $Y$ are independent. To do so, check whether the necessary condition relating the probability of the intersection to the product of the individual probabilities is satisfied.
In a study on streaming content consumption among young people, it was observed that the probability that a student is subscribed to platform A is $P(A) = 0.6$, whereas…
In a study on streaming content consumption among young people, it was observed that the probability that a student is subscribed to platform A is $P(A) = 0.6$, whereas the probability that they are subscribed to platform B is $P(B) = 0.5$. Furthermore, it is known that the probability of not being subscribed to either platform is $P(\bar{A} \cap \bar{B}) = 0.2$.
- a) Calculate the probability that a student is subscribed to both platforms.
- b) Determine whether the events "being subscribed to platform A" and "being subscribed to platform B" are independent events. Justify your answer by comparing $P(A \cap B)$ with $P(A) \times P(B)$.
Consider two events $A$ and $B$ of a random experiment with the following known probabilities: $P(A) = 0.5$, $P(B | A) = 0.4$ and $P(B | \bar{A}) = 0.4$. a) Calculate…
Consider two events $A$ and $B$ of a random experiment with the following known probabilities: $P(A) = 0.5$, $P(B | A) = 0.4$ and $P(B | \bar{A}) = 0.4$.
- a) Calculate $P(A \cap B)$ and $P(\bar{A} \cap B)$.
- b) From the previous results, calculate $P(B)$.
- c) Show whether the events $A$ and $B$ are independent. What conclusion can you draw about the probability of $B$ when it does not change whether or not we know that $A$ has occurred?
Dependent events
Two cards are drawn successively and without replacement from a Spanish deck of 40 cards (there are 4 Kings). Let the events be: $A$: "The first card is a King". $B$:…
Two cards are drawn successively and without replacement from a Spanish deck of 40 cards (there are 4 Kings). Let the events be:
-
$A$: "The first card is a King".
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$B$: "The second card is a King".
The tree diagram shows the situation. The probabilities of the first draw are already written; the ones for the second draw, marked with «?», you have to determine yourself.
Calculate the probability of $B$ conditioned on $A$, that is, $P(B|A)$. Is this probability equal to the probability of getting a King on the first draw? Justify whether the events are dependent or independent.
A sportswear brand knows that $70\%$ of its customers buy running shoes. Of those who buy running shoes, $40\%$ also purchase a performance T-shirt. On the other hand,…
A sportswear brand knows that $70\%$ of its customers buy running shoes. Of those who buy running shoes, $40\%$ also purchase a performance T-shirt. On the other hand, among those who do not buy running shoes, only $15\%$ purchase the performance T-shirt.
- a) If we choose a customer at random, what is the probability that they buy the performance T-shirt?
- b) Are the events "buying running shoes" and "buying a T-shirt" independent? Reason your answer by analyzing whether buying running shoes changes the probability of buying the T-shirt.
A digital content creator has two channels: one for video games ($V$) and one for cooking ($C$). $60\%$ of their subscribers follow channel $V$, $40\%$ follow channel…
A digital content creator has two channels: one for video games ($V$) and one for cooking ($C$). $60\%$ of their subscribers follow channel $V$, $40\%$ follow channel $C$ and $20\%$ follow both channels.
- a) If we randomly select a subscriber who is known to follow the cooking channel, what is the probability that they also follow the video games channel?
- b) In light of the data, would you say that following one channel influences the probability of following the other? Justify whether the events are dependent or independent.
Multi-step problems
When there are dependent stages, the tree diagram helps: you multiply along each branch and add across the branches that lead to the requested event. Tables and Venn diagrams are also useful.
In a school, $45\%$ of the 2nd-year Bachillerato students are in the Social Sciences track ($CS$), $35\%$ in Science and Technology ($CT$), and the rest in Arts ($A$).…
In a school, $45\%$ of the 2nd-year Bachillerato students are in the Social Sciences track ($CS$), $35\%$ in Science and Technology ($CT$), and the rest in Arts ($A$). It is known that the probability that a student likes statistics is $0.8$ if they are in $CS$, $0.6$ if they are in $CT$, and $0.3$ if they are in $A$.
- a) Draw the tree diagram that represents this situation, indicating the probability on each branch.
- b) Is liking statistics an event independent of the Bachillerato track studied? Prove it mathematically for the case of the Social Sciences track.
Let $A$ and $B$ be two events such that $P(A) = 0.4$ and $P(B) = 0.3$. a) If $A$ and $B$ are independent events, calculate $P(A \cup B)$ and $P(A | B)$. b) If $A$ and…
Let $A$ and $B$ be two events such that $P(A) = 0.4$ and $P(B) = 0.3$.
- a) If $A$ and $B$ are independent events, calculate $P(A \cup B)$ and $P(A | B)$.
- b) If $A$ and $B$ are dependent events and we know that $P(A \cap B) = 0.2$, calculate $P(B | A)$.
- c) In case b), are $A$ and $B$ mutually exclusive events? Justify your answer.
Traffic accidents in a city have been classified according to the type of vehicle and whether the driver was under 25 years old. The data are shown in the following…
Traffic accidents in a city have been classified according to the type of vehicle and whether the driver was under 25 years old. The data are shown in the following table:
| Car ($T$) | Moped ($M$) | TOTAL | |
|---|---|---|---|
| Under 25 years old ($J$) | $12$ | $18$ | $30$ |
| Over 25 years old ($V$) | $48$ | $22$ | $70$ |
| TOTAL | $60$ | $40$ | $100$ |
- a) If we choose an accident at random, what is the probability that the driver is under 25 years old?
- b) Given that the accident involved a moped, what is the probability that the driver is under 25 years old?
- c) Using the previous results, explain with reasons whether the events "being under 25 years old" and "driving a moped" are independent.
Let $A$ and $B$ be two events of a random experiment such that $P(A^c \cap B^c) = 0.2$, $P(A | B) = 0.4$ and $P(B | A) = 0.5$. a) Calculate the probabilities of events…
Let $A$ and $B$ be two events of a random experiment such that $P(A^c \cap B^c) = 0.2$, $P(A | B) = 0.4$ and $P(B | A) = 0.5$.
- a) Calculate the probabilities of events $A$ and $B$. (Hint: use the definition of conditional probability to set up a system of equations).
- b) Determine whether events $A$ and $B$ are independent. Justify your answer.
- c) Calculate $P(A^c \cup B)$.
In a video game tournament, a player must pass two stages. The probability of passing the first stage is $0.7$. If they pass the first, the probability of passing the…
In a video game tournament, a player must pass two stages. The probability of passing the first stage is $0.7$. If they pass the first, the probability of passing the second is $0.5$. If they do not pass the first, they are given a second-chance playoff ("repesca") opportunity which they pass with probability $0.3$. If they pass the playoff, they enter the second stage, but with a success probability of only $0.2$ due to accumulated fatigue.
- a) Calculate the probability that the player ultimately passes the tournament (passes the second stage).
- b) If the player has passed the tournament, what is the probability that they did so without needing to go through the playoff?
Back to the beginning: the coin and the die are independent because $P(A\cap B)=P(A)P(B)$; the cards that are not put back are dependent because the second probability changes with the first.