2. The random variable X is sum of the dice when 2 balanced dice are rolled. 2 3 4 7 8 9. 10 11 12 P(X=x) 1/36 1/18 1/12 1/9 5/36 1/6 5/36 1/9 1/12 1/18 1/36 g. Find the mean of the sum of the dice. h. Find the standard deviation for the sum of the dice.

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### Probability Distribution for the Sum of Two Dice

The random variable \( X \) represents the sum of the numbers on two balanced dice when rolled. The probability distribution table for \( X \) is as follows:

| \( X \)      | 2    | 3    | 4    | 5    | 6    | 7    | 8    | 9    | 10   | 11   | 12   |
|--------------|------|------|------|------|------|------|------|------|------|------|------|
| \( P(X=x) \) | 1/36 | 1/18 | 1/12 | 1/9  | 5/36 | 1/6  | 5/36 | 1/9  | 1/12 | 1/18 | 1/36 |

#### Tasks:

**g. Find the mean of the sum of the dice.**

To find the mean (or expected value) \( E(X) \) of the sum of the dice, use the formula:

\[ E(X) = \sum (x \cdot P(X=x)) \]

**h. Find the standard deviation for the sum of the dice.**

First, find the variance \( \text{Var}(X) \) using:

\[ \text{Var}(X) = \sum (x^2 \cdot P(X=x)) - [E(X)]^2 \]

Then, calculate the standard deviation by taking the square root of the variance:

\[ \text{Standard Deviation} = \sqrt{\text{Var}(X)} \]
Transcribed Image Text:### Probability Distribution for the Sum of Two Dice The random variable \( X \) represents the sum of the numbers on two balanced dice when rolled. The probability distribution table for \( X \) is as follows: | \( X \) | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |--------------|------|------|------|------|------|------|------|------|------|------|------| | \( P(X=x) \) | 1/36 | 1/18 | 1/12 | 1/9 | 5/36 | 1/6 | 5/36 | 1/9 | 1/12 | 1/18 | 1/36 | #### Tasks: **g. Find the mean of the sum of the dice.** To find the mean (or expected value) \( E(X) \) of the sum of the dice, use the formula: \[ E(X) = \sum (x \cdot P(X=x)) \] **h. Find the standard deviation for the sum of the dice.** First, find the variance \( \text{Var}(X) \) using: \[ \text{Var}(X) = \sum (x^2 \cdot P(X=x)) - [E(X)]^2 \] Then, calculate the standard deviation by taking the square root of the variance: \[ \text{Standard Deviation} = \sqrt{\text{Var}(X)} \]
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