This editor is interactive! Try changing the code.

`lognormal(mu, sigma)`

is a normal distribution with
mean `mu`

and standard deviation `sigma`

. For example, these two distributions
are identical:
`5 to 10`

does the same thing as `to(5,10)`

.
- ) => list
```
```squiggle
List.flatten([
[1, 2],
[3, 4],
]) // [1,2,3,4]
```
---
description: Sample set distributions are one of the three distribution formats. Internally, they are stored as a list of numbers.
---
# Sample Set Distribution
Sample set distributions are one of the three distribution formats. Internally, they are stored as a list of numbers. It's useful to distinguish point set distributions from arbitrary lists of numbers to make it clear which functions are applicable.
Monte Carlo calculations typically result in sample set distributions.
All regular distribution function work on sample set distributions. In addition, there are several functions that only work on sample set distributions.
### fromDist
```
SampleSet.fromDist: (distribution) => sampleSet
```
### fromList
```
SampleSet.fromList: (list

`normal(5,2) .- uniform(10,12)`

results in a distribution-like
object with negative probability mass.
- >
```
```squiggle
Dict.toList({ foo: 3, bar: 20 }) // [["foo", 3], ["bar", 20]]
```
### fromList
```
Dict.fromList: (list

- >) => dict<'a>
```
```squiggle
Dict.fromList([
["foo", 3],
["bar", 20],
]) // {foo: 3, bar: 20}
```
### keys
```
Dict.keys: (dict<'a>) => list