I also have these data (admittedly the first one is from 2010 not 2011) 😉

Indeed. I really like the 'Train-the-Trainer' module too.

Yup, its a really good first step. And maybe encourages better interoperability etc going forward.

Looks like this project is just a list of links to datasets, mostly on OSF, so there's no attempts at harmonizing or curation (beyond links). It should still be useful given how difficult it can be to find relevant datasets.

What does this do? Allow you to write

```{r}
#| fig-cap: Number of participants was {data$n}.
```

?

Eläkeläiset lol, why?

And that's a fine conclusion too (if we can be confident in it) and should directly inform the next experiment (probably need way more participants then.)

Thanks, interesting paper. I'm missing a conclusion in the example write-up. Is it that the hypotheses (JND & prior SD) are so uncertain that there cannot be a conclusion? I find this generally the stickiest point against interval tests.

I am not averse to the S value, and I like how it converts the question to one of quantifying information. It would be lovely to see some experiments evaluating whether it could deliver (so comparing interpretations & decisions against p values etc.)

Looks great, I'll read tmrw. I am not sure what the panda thing is though! avi why not use a more modern video codec

😢

Who said stats is hard!

So if I flip it I can then say null is equally probable as x *tails* in a row 🥴

If the null is true these results (or more extreme) have the same surprisal value as x heads in a row? Am I reading this right?