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(14.1) Random Variables

A fair 6-sided die

In the last unit, we looked at various probabilities when rolling a fair 6-sided die.
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Give your answers as fractions.

$P\left(\text{rolling a 3}\right)=$

$P\left(\text{rolling a 7}\right)=$

$P\left(\text{rolling a number greater than 1}\right)=$
For this experiment, we can let $X$ represent the number that is rolled.
For example, $P\left(\text{rolling a 3}\right)$ can be written $P\left(X=3\right)$.

Write the following using $X$.

$P\left(\text{rolling a 6}\right)$ can be written .

$P\left(\text{rolling a number greater than 1}\right)$ can be written

$P\left(\text{rolling a number greater than 2 and less than or equal to 5}\right)$ can be written

Find the following probabilities. Give your answers as fractions.

$P\left(X=1\right)=$ .

$P\left(X\lt 3\right)=$

$P\left(3\le X\lt 6\right)=$

Two fair 6-sided dice

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For this experiment where we roll two fair 6-sided dice, let $X$ represent the number of sixes rolled.
For example, $P\left(X=2\right)$ means the probability of rolling 2 sixes.

Find the following probabilities. Give your answers as fractions.

$P\left(X=2\right)=$ .

$P\left(X=1\right)=$

$P\left(X=0\right)=$

We can use a table to organize this information.
$x$ $0$ $1$ $2$
$P\left(X=x\right)$

Notice that we used $x$ as a variable for the possible outcomes and found $P\left(X=x\right)$.

For this same experiment where we roll two fair 6-sided dice, let $Z$ represent the sum of the two numbers rolled.
For example, $P\left(Z=12\right)$ means the probability of the sum of the two numbers equaling 12.

Find the following probabilities. Give your answers as fractions.

$P\left(Z=3\right)=$ .

$P\left(Z=7\right)=$

$P\left(Z\ge 9\right)=$

$P\left(3\le Z\lt 12\right)=$

We can use a table to organize the information.
$z$ $2$ $3$ $4$ $5$ $6$ $7$ $8$ $9$ $10$ $11$ $12$
$P\left(Z=z\right)$

A table that contains the probabilities for all possible outcomes is called a

Each probability must be between $\le P\left(X=x\right) \le$ .

The sum of all the probabilities is $\sum P\left(X=x\right)=$ .