Posts

D&D.Sci II: The Sorceror's Personal Shopper 2021-01-12T01:38:44.168Z
D&D.Sci Evaluation and Ruleset 2020-12-12T15:00:20.984Z
D&D.Sci 2020-12-05T23:26:40.934Z
Model Depth as Panacea and Obfuscator 2020-11-09T00:02:03.297Z
Ductive Defender: a probability game prototype 2019-03-30T12:31:37.629Z
Case Study II 2018-09-30T00:37:32.974Z
Applying Bayes to an incompletely specified sample space 2018-07-29T17:33:53.978Z
Excessive EDA Effortposting 2018-06-03T19:17:22.595Z
ProbDef: a game about probability and inference 2018-01-02T00:22:03.287Z

Comments

Comment by abstractapplic on D&D.Sci II: The Sorceror's Personal Shopper · 2021-01-13T00:14:50.618Z · LW · GW

From your knowledge of wizardly adherence to habit, the way he never suggested getting items anywhere but the caravans, your knowledge of local markets, and the fact that everyone selling seems to recognize the Owle owl following you, you can be pretty sure that Wakalix bought all 836 of the items on his list from the same source(s) you're currently considering.

(Regarding the other implications of your question, I neither confirm nor deny anything.)

Comment by abstractapplic on D&D.Sci II: The Sorceror's Personal Shopper · 2021-01-12T14:43:45.784Z · LW · GW

Nope.

Comment by abstractapplic on D&D.Sci II: The Sorceror's Personal Shopper · 2021-01-12T13:19:20.739Z · LW · GW

Fun thought, but no. In fact, none of the available magic items can help you in that way.

Comment by abstractapplic on D&D.Sci II: The Sorceror's Personal Shopper · 2021-01-12T03:42:38.071Z · LW · GW

Somehow forgot to link to dataset in OP, fixed now.

Comment by abstractapplic on D&D.Sci · 2020-12-07T13:40:24.146Z · LW · GW

I generated the dataset. The rules I used to do so will be provided on Saturday, so everyone can see how close they got to the truth.

Comment by abstractapplic on D&D.Sci · 2020-12-07T11:30:17.700Z · LW · GW

No to both questions.

Comment by abstractapplic on D&D.Sci · 2020-12-06T17:59:44.679Z · LW · GW

Your interpretation is correct: there are no character classes in this world.

Comment by abstractapplic on D&D.Sci · 2020-12-06T02:51:28.245Z · LW · GW

No.

Comment by abstractapplic on D&D.Sci · 2020-12-06T02:48:22.783Z · LW · GW

I've added some guidelines to the main post. Thanks for asking, I'm embarrassed to admit that angle didn't occur to me.

Comment by abstractapplic on D&D.Sci · 2020-12-06T02:38:26.105Z · LW · GW

Your paranoia does you credit, but I'm not doing anything close to that subtle; what you're seeing is Pandas putting the columns in alphabetical order when saving the dataset as csv. (I had to manually edit it to make 'results' be the last row instead of third-to-last)

Comment by abstractapplic on Model Depth as Panacea and Obfuscator · 2020-11-13T11:42:37.344Z · LW · GW

Sorry, yes, good catch. Edited now.

Comment by abstractapplic on Excessive EDA Effortposting · 2018-06-06T18:01:08.774Z · LW · GW

Responses to your differences:

.I hear you, but R has enough fully-automated testing tools that it's much simpler for me to just run the appropriate test and see what pops out the other end. (Also, THANK YOU for mentioning Chebyshev, I can't believe I'd never heard of that inequality before and it's EXACTLY my kind of thing)

.I think (?) you're operating on the wrong level of meta here. A t-test uses both the mean and the variance of the distribution(s) you feed it, and that's true whether or not it's being used to test a correlation. The CLT will not save us, because the single (admittedly gaussian-distributed) datapoint representing the mean has a variance of zero. (Something I could have done - in fact, something I remember doing much earlier in my career, back when I was better at identifying problems than finding expedient solutions - was to group not-necessarily-normal datapoints together into batches of about twenty, take the averages per-batch, and then t-test the lists of those: it was a ridiculous waste of statistical power, but it was valid!)

.That's an excellent idea. My excuse for not doing that is that I was prioritising pointedly-not-getting-things-wrong over actually-getting-things-right; my reason is that I just didn't think of it and I'm too lazy (and data-purist) to go back and try that now.

The dataset is, at time of writing, still up at https://gist.github.com/ncase/74ae97cb74893a0c540274b44f550503. I'd love to see what you throw at it.

Comment by abstractapplic on ProbDef: a game about probability and inference · 2018-01-07T00:14:02.965Z · LW · GW

Thanks for the detailed feedback! You should be pleased to know the next iteration will make the utility of captured mines a lot more obvious, and do so a lot earlier (this is a pretty common complaint). Also, if you liked keeping track of decoys in your head, I should probably make sure you know you can turn the autocalc off in the Options menu & get the same sort of experience with the Bayesian levels.

Comment by abstractapplic on ProbDef: a game about probability and inference · 2018-01-06T23:46:01.713Z · LW · GW

Please don't take this the wrong way, but: if you liked it, why did you stop playing?

I ask because this is a recurring theme I've noticed: people saying it's fun & well-put-together (and appearing to mean it), but that they're not motivated to keep going. Or, in other words, that it's engaging but not compelling.

I'm pretty sure it comes down to the absence of story, context and overarching goals. But if the cause of this effect is something different, I really want to know.

Comment by abstractapplic on ProbDef: a game about probability and inference · 2018-01-06T23:30:49.448Z · LW · GW

Good catch! I have a bunch of minor tweaks I want to make to this version of the game before moving on, I'll add that to it.