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Randomness and probability · Discrete distributions. Binomial distribution (BIN)

Random variable

Up to now, probability has been calculated for events ("drawing an ace", "it rains"). But many real questions are numerical: how many breakdowns will there be this week? How much is won in this raffle? How many bits will arrive correctly? A random variable is the tool that turns the outcome of a random experiment into a number, so that we can calculate with it: add it, average it, see how spread out it is.

Before you start, make sure you know: One-variable descriptive statistics (1st Bachillerato)
Before you start, make sure you know: Definitions (1st Bachillerato)

What a random variable is

Diagram of a discrete random variable that assigns numerical values from 1 to 4 to the outcomes of an experiment. Experiment: generate a number from 1 to 4, equally likely outcome X (number) Here X is already the number generated itself: 1, 2, 3 or 4. Discrete: isolated values (no meaningful decimal values in between).

This section deals only with discrete variables; at the end of the topic the continuous variable is briefly introduced, and it will be developed further with the normal distribution.

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A random number app generates integers from $1$ to $4$, all with equal probability. Let $X$ be the number generated. a) Write down the probability function of $X$ in…

A random number app generates integers from $1$ to $4$, all with equal probability. Let $X$ be the number generated.

  1. a) Write down the probability function of $X$ in table form.
  2. b) Calculate the mean $\mu$.
  3. c) Calculate the standard deviation $\sigma$, rounding to two decimal places.
Solve

Probability function

To describe a discrete random variable completely, it is enough to say what probability each of its possible values has.

Bar chart representing the point probability function of a discrete random variable. x₁x₂ x₃x₄ The sum of the heights (probabilities) must be exactly 1
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A discrete random variable $X$ takes the values $1$, $2$, $3$ and $4$ with this incomplete probability function: | $x_i$ | $1$ | $2$ | $3$ | $4$ | |---|---|---|---|---|…

A discrete random variable $X$ takes the values $1$, $2$, $3$ and $4$ with this incomplete probability function:

$x_i$ $1$ $2$ $3$ $4$
$p_i$ $0,15$ $k$ $0,35$ $0,25$
  1. a) Calculate the value of $k$.
  2. b) Find $P[X \ge 3]$.
  3. c) Find $P[X < 2]$.
Solve
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State, giving reasons, which of the following tables can represent the probability function of a discrete random variable: Table 1: values $1$, $2$, $3$ with…

State, giving reasons, which of the following tables can represent the probability function of a discrete random variable:

  • Table 1: values $1$, $2$, $3$ with probabilities $0,3$; $0,4$; $0,2$.

  • Table 2: values $1$, $2$, $3$, $4$ with probabilities $0,5$; $0,3$; $0,3$; $-0,1$.

  • Table 3: values $1$, $2$, $3$, $4$ with probabilities $0,25$; $0,25$; $0,25$; $0,25$.

In each case, state the condition (or conditions) that are satisfied or violated.

Solve

Distribution function

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

Step graph of the cumulative distribution function F(x) with jump discontinuities at each value of the variable. 01 23 F(x)
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The cumulative distribution function of a discrete random variable $X$ is given by: $F(0) = 0,2 \qquad F(1) = 0,5 \qquad F(2) = 0,8 \qquad F(3) = 1$ a) Calculate…

The cumulative distribution function of a discrete random variable $X$ is given by:

$F(0) = 0,2 \qquad F(1) = 0,5 \qquad F(2) = 0,8 \qquad F(3) = 1$

  1. a) Calculate $P[X \le 2]$.
  2. b) Calculate $P[X = 2]$.
  3. c) Calculate $P[X > 1]$.
Solve
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The figure shows the cumulative distribution function $F(x)$ of a discrete random variable $X$ that takes the values $0$, $1$, $2$ and $3$. a) Deduce from the graph the…

The figure shows the cumulative distribution function $F(x)$ of a discrete random variable $X$ that takes the values $0$, $1$, $2$ and $3$.

−1 0 1 2 3 4 x 0,2 0,5 0,8 1 y F(x)
  1. a) Deduce from the graph the probability function of $X$ (the values $p_i = P[X = x_i]$) and write it down in table form.
  2. b) Calculate $P[1 \le X < 3]$ using the cumulative distribution function.
  3. c) Find the mean of $X$.
Solve

Mean, variance and standard deviation

Just as a table of statistical data has a mean and a standard deviation, a random variable has its own parameters, calculated using probabilities instead of frequencies.

Representation of the mean or expected value as the balance point of a discrete distribution. μ the mean may not coincide with any value of X
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In a bag for a board game there are $20$ point cards: $6$ cards with a $1$, $4$ cards with a $2$ and $10$ cards with a $3$. A card is drawn at random and its score $X$…

In a bag for a board game there are $20$ point cards: $6$ cards with a $1$, $4$ cards with a $2$ and $10$ cards with a $3$. A card is drawn at random and its score $X$ is noted.

  1. a) Write down the probability function of $X$ in table form.
  2. b) Calculate the mean $\mu$ and interpret it: what average score per card can be expected in the long run?
  3. c) Calculate the standard deviation $\sigma$, rounding to two decimal places.
Solve
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Amina is studying the variable $X$ = "number of weekly breakdowns of a photocopier", with this probability distribution: | $x_i$ | $0$ | $1$ | $2$ | $3$ |…

Amina is studying the variable $X$ = "number of weekly breakdowns of a photocopier", with this probability distribution:

$x_i$ $0$ $1$ $2$ $3$
$p_i$ $0,1$ $0,3$ $0,4$ $0,2$

She has calculated the mean, $\mu = 1,7$, and then wrote:

«$\sigma^2 = \sum p_i \cdot x_i^2 - \mu = 3,7 - 1,7 = 2 \implies \sigma = \sqrt{2} \approx 1,41$»

  1. a) Check her calculation of $\sum p_i \cdot x_i^2$ and confirm that it is correct.
  2. b) Locate the error in the formula she applied for the variance and correct it.
  3. c) Calculate the correct standard deviation.
Solve

Expected value as a criterion: games and raffles

The expected value has a very practical interpretation: it tells you what happens "on average, if it is repeated many times". It is the tool for deciding whether a game, a raffle or a bet is worthwhile.

Comparison of the fairness criterion in games of chance depending on whether the expected average gain is less than, equal to or greater than zero. E[G] < 0 E[G] = 0 (fair) E[G] > 0 Unfavourable you lose on average in the long run Fair you neither win nor lose Favourable you win on average in the long run
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The PTA of a secondary school organises a charity raffle: it sells $200$ tickets at $2\ \text{€}$ each, with one prize of $100\ \text{€}$, four prizes of $25\ \text{€}$…

The PTA of a secondary school organises a charity raffle: it sells $200$ tickets at $2\ \text{€}$ each, with one prize of $100\ \text{€}$, four prizes of $25\ \text{€}$ and ten prizes of $5\ \text{€}$.

  1. a) Write down the probability function of the variable $G$ = "net winnings from buying a ticket" (value of the prize minus the $2\ \text{€}$ it costs).
  2. b) Calculate the expected value of $G$.
  3. c) Interpret the sign of the result: if the expected value is negative, where does that money go? Does that contradict the charitable purpose of the raffle?
Solve
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At a fairground stall, a game is played with two cubic dice: you win $12\ \text{€}$ if you roll doubles (both dice the same), $6\ \text{€}$ if the sum is $7$, and…

At a fairground stall, a game is played with two cubic dice: you win $12\ \text{€}$ if you roll doubles (both dice the same), $6\ \text{€}$ if the sum is $7$, and nothing in any other case.

  1. a) Calculate the probability of winning each prize and the probability of winning nothing. (Note that rolling doubles and having a sum of $7$ are mutually exclusive events; why?)
  2. b) Find the expected value of the prize per game and deduce what the price of the stake should be for the game to be fair.
  3. c) If the stall charges $4\ \text{€}$ per game, who does the game favour? How much is a player who plays $100$ games expected to win or lose?
Solve

Linear transformations and the continuous variable

Diagram of the effect of a linear transformation Y = aX + b on the mean and the standard deviation. μₓ, σₓ Y=a·X+b μY = a·μₓ + b σY = |a|·σₓ

So far $X$ has taken isolated values (discrete). When a quantity can take any value in an interval —a time, a length, a weight— a continuous variable is needed: instead of a table of probabilities, a density function $f(x)$ is used, and the probability of an interval is the area under $f$ between its endpoints (the total area equals $1$, just as $\sum p_i=1$ in the discrete case).

Graph of a continuous density function showing the probability between two points as the area under the curve. ab area = P[a≤X≤b] f(x) in the continuous case there are no "bars": there is an area under a curve
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Let $X$ be a discrete random variable with mean $\mu$ and standard deviation $\sigma$, and let $Y = a \cdot X + b$ be a new variable obtained by applying a linear…

Let $X$ be a discrete random variable with mean $\mu$ and standard deviation $\sigma$, and let $Y = a \cdot X + b$ be a new variable obtained by applying a linear transformation to $X$.

  1. a) Prove, from the definition of the mean, that $\mu_Y = a \cdot \mu + b$.
  2. b) Prove that $\sigma_Y = |a| \cdot \sigma$. Why does the constant $b$ not affect the spread?
  3. c) Application: in an exam, the marks have a mean of $6,2$ and a standard deviation of $1,4$. The teacher decides to transform each mark $X$ into $Y = 0,9 \cdot X + 1$. Calculate the new mean and the new standard deviation.
Solve
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The time (in minutes) it takes for a server to boot after a restart is a continuous random variable $X$ with probability density function $f(x) = k \cdot x$ for…

The time (in minutes) it takes for a server to boot after a restart is a continuous random variable $X$ with probability density function $f(x) = k \cdot x$ for $x \in [0, 4]$ and $f(x) = 0$ elsewhere, represented in the figure.

x y 0 1 2 3 4 ? h = ? f(x) = k · x Area = 1
  1. a) Calculate the value of $k$ knowing that the total area under the probability density function must be $1$.
  2. b) Find the probability that the server takes less than $2$ minutes to boot.
  3. c) Calculate the median of $X$ (the value $m$ such that $P[X \le m] = \frac{1}{2}$) and the mean $\mu$. Which of the two is greater? What do you think is the reason for this?
Solve

Back to the start: The number of breakdowns or the result of a raffle cannot be predicted with certainty for a single case, but the expected value ($E[X]$ or $E[G]$) determines exactly what to expect on average in the long run.

Summary

See all the exercises in this section