Definitions
So far probability has been used intuitively: "favourable outcomes over possible outcomes". But that rule only works if all the outcomes are equally likely, and it does not explain why $P(\overline{A}) = 1-P(A)$ or why $P(A \cup B) = P(A)+P(B)-P(A\cap B)$ always work. The mathematician Andrey Kolmogorov formalised probability in 1933 using just three starting rules (the axioms); everything else, including Laplace's rule, follows from them.
Probability as a function: Kolmogorov's axioms
A high school drama club decides to raffle three tickets for its premiere among the audience. To do so, it uses a drum containing balls numbered from $1$ to $20$.…
A high school drama club decides to raffle three tickets for its premiere among the audience. To do so, it uses a drum containing balls numbered from $1$ to $20$. Consider the random experiment of drawing one ball and noting its number.
Define the following elements:
- a) The sample space $E$.
- b) The event $A$: "getting a number that is a multiple of $5$".
- c) The event $B$: "getting a prime number greater than $10$".
- d) The event $C$: "getting a number less than $4$".
Write all the elementary events that make up each of the sets above.
Laplace's rule: a particular case that satisfies the axioms
Laplace's rule is not a separate law: it is the form that $P$ takes when the $n$ outcomes of $E$ are equally likely. Checking that it satisfies the three axioms gives confidence in why it works.
In an urn there are $12$ coloured balls: $5$ are red, $4$ are blue and $3$ are yellow. We draw a ball at random and observe its colour. Using Laplace's rule, calculate…
In an urn there are $12$ coloured balls: $5$ are red, $4$ are blue and $3$ are yellow. We draw a ball at random and observe its colour. Using Laplace's rule, calculate the probability of the following events:
- a) $P(R)$: "the ball is red".
- b) $P(A \cup M)$: "the ball is blue or yellow".
- c) $P(\bar{R})$: "the ball is not red".
- d) $P(V)$: "the ball is green".
Properties that follow from the axioms
None of these rules is a new axiom: they can all be proved from Kolmogorov's three axioms, and that is why they are always valid, whether the outcomes are equally likely or not.
A music app has analysed the preferences of a group of young people. It is known that the probability that a user likes Trap is $P(T) = 0,65$, the probability that they…
A music app has analysed the preferences of a group of young people. It is known that the probability that a user likes Trap is $P(T) = 0,65$, the probability that they like Pop is $P(P) = 0,40$ and the probability that they like both genres is $P(T \cap P) = 0,15$.
Calculate the probability that, when choosing a user at random:
- a) They like Trap or Pop.
- b) They do not like Trap.
- c) They like Trap but not Pop ($P(T - P)$).
On a streaming platform, $65\ \%$ of the subscribers have watched the latest season of a sci-fi series ($S$), $40\ \%$ have watched a nature documentary ($D$) and…
On a streaming platform, $65\ \%$ of the subscribers have watched the latest season of a sci-fi series ($S$), $40\ \%$ have watched a nature documentary ($D$) and $25\ \%$ have watched both. If we select a user at random, calculate the probability of the following events:
a) That they have watched the series or the documentary.
b) That they have watched neither the series nor the documentary.
c) That they have watched the series but not the documentary.
Venn diagrams with areas proportional to probability
A Venn diagram can be drawn so that the area of each region is proportional to its probability: a visual way of checking that the calculations are consistent with the axioms (the whole of $E$ has total area $1$).
State with justification whether the following probability assignments for a sample space $E = \{x_1, x_2, x_3\}$ are valid according to Kolmogorov's axioms: a)…
State with justification whether the following probability assignments for a sample space $E = \{x_1, x_2, x_3\}$ are valid according to Kolmogorov's axioms:
- a) $P(x_1) = 0,4; \quad P(x_2) = 0,3; \quad P(x_3) = 0,3$
- b) $P(x_1) = 0,7; \quad P(x_2) = -0,1; \quad P(x_3) = 0,4$
- c) $P(x_1) = 0,5; \quad P(x_2) = 0,5; \quad P(x_3) = 0,2$
- d) $P(x_1) = 1; \quad P(x_2) = 0; \quad P(x_3) = 0$
A survey was conducted among secondary school students regarding their use of social media. It is known that the probability that a student uses Instagram ($I$) is…
A survey was conducted among secondary school students regarding their use of social media. It is known that the probability that a student uses Instagram ($I$) is $P(I) = 0,82$ and the probability that they use TikTok ($T$) is $P(T) = 0,55$. If the probability that they use neither is $P(\bar{I} \cap \bar{T}) = 0,10$, use De Morgan's laws to calculate:
a) The probability that they use at least one of the two social media platforms.
b) The probability that they use both simultaneously.
c) Are the events "using Instagram" and "using TikTok" incompatible? Give reasons for your answer.
Bounds on probability without knowing the intersection
The axioms do not only give equalities: they also let us bound an unknown probability when information is missing, using the fact that no probability can exceed $1$ or be negative.
Given two events $A$ and $B$ associated with the same random experiment, we know that the probability that neither occurs is $P(\bar{A} \cap \bar{B}) = 0,2$.…
Given two events $A$ and $B$ associated with the same random experiment, we know that the probability that neither occurs is $P(\bar{A} \cap \bar{B}) = 0,2$. Furthermore, it is known that $P(A) = 0,5$ and that the probability that $A$ occurs but $B$ does not occur is $P(A - B) = 0,3$.
Calculate step-by-step, using the properties of probability and De Morgan's laws:
- a) $P(A \cup B)$
- b) $P(A \cap B)$
- c) $P(B)$
- d) $P(\bar{A} \cup \bar{B})$