diff --git a/packages/website/docs/Guides/DistributionCreation.mdx b/packages/website/docs/Guides/DistributionCreation.mdx
index 23a4bf0e..075f036d 100644
--- a/packages/website/docs/Guides/DistributionCreation.mdx
+++ b/packages/website/docs/Guides/DistributionCreation.mdx
@@ -17,7 +17,7 @@ The `to` function is an easy way to generate simple distributions using predicte
If both values are above zero, a `lognormal` distribution is used. If not, a `normal` distribution is used.
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When 5 to 10
is entered, both numbers are positive, so it
generates a lognormal distribution with 5th and 95th percentiles at 5 and
@@ -74,7 +74,7 @@ If both values are above zero, a `lognormal` distribution is used. If not, a `no
The `mixture` mixes combines multiple distributions to create a mixture. You can optionally pass in a list of proportional weights.
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@@ -139,7 +139,7 @@ mx(forecast, forecast_if_completely_wrong, [1-chance_completely_wrong, chance_co
Creates a [normal distribution](https://en.wikipedia.org/wiki/Normal_distribution) with the given mean and standard deviation.
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@@ -234,7 +234,7 @@ with values at 1 and 2. Therefore, this is the same as `mixture(pointMass(1),poi
`pointMass()` distributions are currently the only discrete distributions accessible in Squiggle.
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@@ -263,7 +263,7 @@ with values at 1 and 2. Therefore, this is the same as `mixture(pointMass(1),poi
Creates a [beta distribution](https://en.wikipedia.org/wiki/Beta_distribution) with the given `alpha` and `beta` values. For a good summary of the beta distribution, see [this explanation](https://stats.stackexchange.com/a/47782) on Stack Overflow.
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@@ -300,7 +300,7 @@ Creates a [beta distribution](https://en.wikipedia.org/wiki/Beta_distribution) w
Examples
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