# dice: Theoretical Probability Distribution of Rolling Dice In clttools: Central Limit Theorem Experiments (Theoretical and Simulation)

## Description

Mean and probability of rolling fair or loaded dice

## Usage

 `1` ```dice(n, prob = NULL) ```

## Arguments

 `n` number of trials `prob` probability assigned to each possible outcome

## Details

The default probabilty equals to 1/n. All the assigned probabilites must between 0 and 1.

## Value

Mean value and corresponding probabilities for all possible outcomes.

## Examples

 ```1 2``` ```dice(n = 4) dice(2, c(0.1, 0.2, 0.2, 0.1, 0.3, 0.1)) ```

### Example output

```   MEAN_VALUE  PROBABILITY
1        1.00 0.0007716049
2        1.25 0.0030864198
3        1.50 0.0077160494
4        1.75 0.0154320988
5        2.00 0.0270061728
6        2.25 0.0432098765
7        2.50 0.0617283951
8        2.75 0.0802469136
9        3.00 0.0964506173
10       3.25 0.1080246914
11       3.50 0.1126543210
12       3.75 0.1080246914
13       4.00 0.0964506173
14       4.25 0.0802469136
15       4.50 0.0617283951
16       4.75 0.0432098765
17       5.00 0.0270061728
18       5.25 0.0154320988
19       5.50 0.0077160494
20       5.75 0.0030864198
21       6.00 0.0007716049
MEAN_VALUE PROBABILITY
1         1.0        0.01
2         1.5        0.04
3         2.0        0.08
4         2.5        0.10
5         3.0        0.14
6         3.5        0.18
7         4.0        0.17
8         4.5        0.10
9         5.0        0.11
10        5.5        0.06
11        6.0        0.01
```

clttools documentation built on May 29, 2017, 11:43 p.m.