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				|  | @ -22,17 +22,19 @@ If both values are above zero, a `lognormal` distribution is used. If not, a `no | ||||||
| 
 | 
 | ||||||
| <Tabs> | <Tabs> | ||||||
|   <TabItem value="ex1" label="5 to 10" default> |   <TabItem value="ex1" label="5 to 10" default> | ||||||
|     When `5 to 10` is entered, both numbers are positive, so it generates a |     When <code>5 to 10</code> is entered, both numbers are positive, so it | ||||||
|     lognormal distribution with 5th and 95th percentiles at 5 and 10. |     generates a lognormal distribution with 5th and 95th percentiles at 5 and | ||||||
|  |     10. | ||||||
|     <SquiggleEditor initialSquiggleString="5 to 10" /> |     <SquiggleEditor initialSquiggleString="5 to 10" /> | ||||||
|   </TabItem> |   </TabItem> | ||||||
|   <TabItem value="ex3" label="to(5,10)"> |   <TabItem value="ex3" label="to(5,10)"> | ||||||
|     `5 to 10` does the same thing as `to(5,10)`. |     <code>5 to 10</code> does the same thing as <code>to(5,10)</code>. | ||||||
|     <SquiggleEditor initialSquiggleString="to(5,10)" /> |     <SquiggleEditor initialSquiggleString="to(5,10)" /> | ||||||
|   </TabItem> |   </TabItem> | ||||||
|   <TabItem value="ex2" label="-5 to 5"> |   <TabItem value="ex2" label="-5 to 5"> | ||||||
|     When `-5 to 5` is entered, there's negative values, so it generates a normal |     When <code>-5 to 5</code> is entered, there's negative values, so it | ||||||
|     distribution. This has 5th and 95th percentiles at 5 and 10. |     generates a normal distribution. This has 5th and 95th percentiles at 5 and | ||||||
|  |     10. | ||||||
|     <SquiggleEditor initialSquiggleString="-5 to -3" /> |     <SquiggleEditor initialSquiggleString="-5 to -3" /> | ||||||
|   </TabItem> |   </TabItem> | ||||||
|   <TabItem value="ex4" label="1 to 10000"> |   <TabItem value="ex4" label="1 to 10000"> | ||||||
|  | @ -173,9 +175,10 @@ Creates a [log-normal distribution](https://en.wikipedia.org/wiki/Log-normal_dis | ||||||
|     ❓ Understanding <bold>mu</bold> and <bold>sigma</bold> |     ❓ Understanding <bold>mu</bold> and <bold>sigma</bold> | ||||||
|   </summary> |   </summary> | ||||||
|   <p> |   <p> | ||||||
|     The log of `lognormal(mu, sigma)` is a normal distribution with mean `mu` |     The log of <code>lognormal(mu, sigma)</code> is a normal distribution with | ||||||
|     and standard deviation `sigma`. For example, these two distributions are |     mean <code>mu</code> | ||||||
|     identical: |     and standard deviation <code>sigma</code>. For example, these two distributions | ||||||
|  |     are identical: | ||||||
|   </p> |   </p> | ||||||
|   <SquiggleEditor |   <SquiggleEditor | ||||||
|     initialSquiggleString={`normalMean = 10 |     initialSquiggleString={`normalMean = 10 | ||||||
|  |  | ||||||
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