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BAC1 ss · Mathematics
Probability · Discrete variable distributions

Discrete probability function and distribution function

Almost no real question about a random variable asks for "exactly one value": a company wants to know the probability of receiving at most $2$ complaints a day, an NGO how many volunteers are needed as a minimum to cover at least $10$ shifts, a survey what proportion of respondents hold an opinion or more. To answer questions like these quickly we use the distribution function, which accumulates probabilities.

Before you start, make sure you know: Compound events (4th ESO)
Before you start, make sure you know: First-degree equations (2nd ESO)

Constructing the probability function

Sometimes the probability function is given by an incomplete table, and sometimes by a formula; in both cases we have to use the fact that the probabilities add up to $1$.

Bar chart with four point probabilities that add up to one. x₁x₂ x₃x₄ p₁+p₂+p₃+p₄=1 ⇒ any gap is found by subtraction
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Determine with reasons whether the following table can represent the probability function of a discrete random variable $X$. To do this, check whether the fundamental…

Determine with reasons whether the following table can represent the probability function of a discrete random variable $X$. To do this, check whether the fundamental properties of probabilities are satisfied:

$x_i$ $1$ $2$ $3$ $4$
$P(X = x_i)$ $0,25$ $0,40$ $0,15$ $0,20$
0,1 0,2 0,3 0,4 0,5 1 2 3 4 0,25 0,40 0,15 0,20 xᵢ P(X=xᵢ)
Solve
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A streaming platform analyses the number of series a user watches per week. The discrete random variable $X$ is defined as the "number of completed series". Its…

A streaming platform analyses the number of series a user watches per week. The discrete random variable $X$ is defined as the "number of completed series". Its probability function is given by the following table:

$x_i$ $0$ $1$ $2$ $3$
$P(X = x_i)$ $0,1$ $k$ $0,3$ $0,2$

Find the value of the constant $k$ for the distribution to be well-defined, and calculate the probability that a user watches at least 2 series a week, that is, $P(X \ge 2)$.

Solve
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Let $X$ be a discrete random variable whose probability function is given by: $P(X=x) = \frac{x}{10}$ for $x \in \{1, 2, 3, 4\}$ a) Write the table of values for the…

Let $X$ be a discrete random variable whose probability function is given by:

$P(X=x) = \frac{x}{10}$ for $x \in \{1, 2, 3, 4\}$

  1. a) Write the table of values for the probability function.
  2. b) Check that the sum of all probabilities is equal to $1$.
  3. c) Calculate $P(X \ge 3)$.
Solve

Events with several values

Once the table has been constructed, any probability about $X$ is calculated by adding the $p_i$ of the values we are interested in.

Bar chart of a discrete variable with several values highlighted to represent the probability of a compound event. P(X≤1): light bars P(2≤X≤3): highlighted bars
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Given the following probability function of a discrete random variable $X$, calculate the probabilities requested below: | $x_i$ | $10$ | $20$ | $30$ | $40$ | $50$ | |…

Given the following probability function of a discrete random variable $X$, calculate the probabilities requested below:

$x_i$ $10$ $20$ $30$ $40$ $50$
$p_i$ $0,15$ $0,25$ $0,35$ $0,15$ $0,10$
  1. a) $P(X < 30)$
  2. b) $P(X \le 30)$
  3. c) $P(20 < X \le 40)$
Solve
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A biased six-sided die is rolled, such that the probability of getting an even number is twice that of getting an odd number. If all even numbers are equally likely, and…

A biased six-sided die is rolled, such that the probability of getting an even number is twice that of getting an odd number. If all even numbers are equally likely, and the same applies to odd numbers:

  1. a) Determine the probability function of the random variable $X$ = "outcome obtained when rolling the die".
  2. b) Calculate the probability of getting a value less than or equal to $3$.
  3. c) Calculate the mean or expected value of this distribution.
p 2p P(X) 1 2 3 4 5 6 X Odd Even P(Even) = 2·P(Odd) X ≤ 3
Solve

The distribution function

Sometimes a cumulative probability ("at most this much") is of more interest than the exact value at a single point.

Step graph of the cumulative distribution function showing jumps at each value of the variable. 01 23 F(x)
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Let $X$ be a discrete random variable whose cumulative distribution function $F(x)$ is shown below: $$F(x) = \begin{cases} 0 & \text{if } x < 1 \\ 0,2 & \text{if } 1 \le…

Let $X$ be a discrete random variable whose cumulative distribution function $F(x)$ is shown below:

$$F(x) = \begin{cases} 0 & \text{if } x < 1 \\ 0,2 & \text{if } 1 \le x < 2 \\ 0,5 & \text{if } 2 \le x < 3 \\ 0,9 & \text{if } 3 \le x < 4 \\ 1 & \text{if } x \ge 4 \end{cases}$$
  1. a) From $F(x)$, obtain the probability function $P(X=x_i)$ for each value of the variable.
  2. b) Calculate the probability $P(2 \le X < 4)$.
  3. c) Represent the probability function graphically using a bar chart.

You can do it on paper and send a photo with your answer.

Solve
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A logistics company organizes a darts tournament for its employees. The probability of hitting the red zone is $k$, the blue zone is $2k$ and the white zone is $3k$. If…

A logistics company organizes a darts tournament for its employees. The probability of hitting the red zone is $k$, the blue zone is $2k$ and the white zone is $3k$. If a player throws two darts independently, we define the random variable $X$ as "the number of times the dart hits the red zone".

  1. Find the value of $k$ for the probability distribution to be valid (assume the dart always hits one of the three zones).

  2. Obtain the probability function of $X$.

  3. Calculate the expected number of hits in the red zone if the employee performs $50$ series of two throws each.

Solve

From the distribution function to the probability function

The process also works the other way round: if $F(x)$ is known (for example, as a step graph), the probability table can be reconstructed by reading the size of each jump.

Step graph of the distribution function showing the size of the vertical jumps corresponding to the point probabilities. F(x) step function: 0,2 · 0,5 · 0,8 · 1 jump = p₁ jump = p₂ each vertical jump of F is the probability of that value
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In a workshop specialising in mobile device repair, a study was carried out on the number of devices a technician can fully repair in an eight-hour working day. Let $X$…

In a workshop specialising in mobile device repair, a study was carried out on the number of devices a technician can fully repair in an eight-hour working day. Let $X$ be the random variable expressing this number. The probability function is given by the following table, although one value needs to be completed:

$x_i$ $0$ $1$ $2$ $3$ $4$
$P(X=x_i)$ $0,15$ $0,25$ $0,35$ $k$ $0,05$
  1. a) Calculate the value of $k$ so that the table represents a valid probability distribution.
  2. b) What is the probability that the technician repairs at least two devices in a day?
  3. c) If the workshop receives a productivity bonus on days when more than 2 devices are repaired, what is the probability of receiving this bonus?
0,1 0,2 0,3 0,4 P(X=xᵢ) 0 1 2 3 4 xᵢ (No. of devices) 0,15 0,25 0,35 k 0,05 Σ P(X=xᵢ) = 1
Solve
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A social media content creator analyses the daily number of "unsubscriptions" on their channel. They have found that the probability function of the variable $X$ (number…

A social media content creator analyses the daily number of "unsubscriptions" on their channel. They have found that the probability function of the variable $X$ (number of unsubscriptions) corresponds to the formula $P(X = x) = \frac{k \cdot x}{2^x}$ for $x \in \{1, 2, 3\}$.

  1. Find the exact value of the constant $k$.

  2. Calculate the probability that on a given day there are at least 2 unsubscriptions.

  3. The creator estimates that each unsubscription costs them a loss of $5$ euros in advertising revenue, but gaining a new subscriber earns them $8$ euros. If they gain exactly $3$ new subscribers each day, calculate the expected average profit per day.

Solve

Back to the start: With the distribution function, the probability of receiving "at most $2$ complaints" is simply $F(2)$, and the probability of covering "at least $10$ shifts" is found immediately using the complement: $P(X \geq 10) = 1 - F(9)$.

Summary

See all the exercises in this section