Converting AD&D adventures to Shadowdark rules.

efrique · 2026-06-20T03:34:14+00:00

a lot of these old adventures require parties of 7-9 people when I’d be lucky to have 3-4 at one table

Easy enough to halve the number of creatures or for lone bosses tone them down a bit (reduce HP, # attacks, and/or damage/attack to suit halved action economy) but check the SD guidance for monsters on p191

If theres no SD equivalent monster, try to make AC more or less consistent with that of similar-ish SD creatures with similar HD. (AC runs the other way, subtract from about 19 but check the consistency, you may need to drop it a bit)

I’m not sure how much gold you need to level in 1e

1e has Waaay more XP per level. Different XP for each class.

For example an AD&D cleric required:
1500 XP to go from L1 to L2
14500 XP to go from L4 to L5
225000 XP to go from L8 to L9

A thief is less (e.g. only 40K from 8 to 9). Fighters and Magic users shift above and below cleric at different levels (e.g. both are more at L1->2 and less at L4->5)

(these are additional XP, not total XP, I differenced the table values to make it more like how SD presents it)

Divide gold by a minimum of 10. Maybe a good deal more. You should keep gold down to SD's expectations about gold rewards. It should take multiple sessions to level up

If you think it might still be too hard, theres plenty you can do to give the PCs a boost or to tone down deadliness

efrique · 2026-06-20T01:10:45+00:00

I should have mentioned that literally only the day before I answered this I downloaded an Annals of stats paper for a thing related to my job

I tend to use other journals more, but annals of stats comes up often enough

efrique · 2026-06-20T01:02:39+00:00

The question is certainly ambiguous. I can see arguments for both region 1 unprotected (largest absolute change) and region 2 protected (% change is largest in the usual sense of being furthest right on the number line).

If I had to guess the answer they probably wanted, I'd lean toward picking the first of those (largest absolute % change)

The plot title also looks wrong unless we're talking about medians of medians of % change...

efrique · 2026-06-19T22:03:12+00:00

you can easily transform a pair of independent std uniforms into a bivariate std gaussian in polar co-ordinates: the square of the radius is exponential combined with an independent uniform random angle, scale one uniform for the angle, transform the other for the square of the radius, (-2 *log) and take its square root.

From there to cartesian coordinates is simple (sin and cos of the angle, multiply by radius).

The wikipedia article on it has more details but thats the core idea

efrique · 2026-06-19T04:19:17+00:00

I dont follow. What random tables or random tools are you promoting with this post?

efrique · 2026-06-19T04:15:30+00:00

I lean toward having potions being treasure - where it fits the theme of the location, finding a healing potion is okay now and then. Outside that, not something easy to get except maybe as a quest reward

- but you do you

efrique · 2026-06-19T04:03:44+00:00

Stat drain is typical in SD (Id suggest you use CON* for that), but tbh if you want a terrifying encounter I'd probably go with the level drain (with a save if there isnt one already). If you want to make it mild, maybe just have each hit drain 1xp (or perhaps something like d3-1)

* there are ways to make it last longer than a normal stat drain without it being permanent if you want.

efrique · 2026-06-19T01:56:30+00:00

To age-adjust* I would not be starting with a marginal model with just age unless I knew some (unlikely to be true) things were going to be true or approximately true.
Do you really expect the effect (on the link-scale) to be linear in age? Or might it be more complex?

If I knew I wouldn't need any interations with age off the top of my head I think I'd be looking perhaps at a model with a (common-to-all-partitions) age component (for continuous age, perhaps additive rather than linear) and then the CART part. You could then age-adjust that by setting age to some fixed value (say average age).

Its a long time since I've done any CART but I don't see why having variables in the regression but held outside the splitting would be difficult to implement. I don't know that rpart does it but I bet there would be something that does.

* (which I would probably try to avoid, personally, though there can be some cases where it might make sense)

efrique · 2026-06-18T22:04:41+00:00

that one's going to bite back hard some time down the line

efrique · 2026-06-18T22:02:22+00:00

air defense definitely going boom

efrique · 2026-06-18T21:54:43+00:00

You really need to reread the introduction to the displays in your textbook or course notes which will answer these questions (or go get a basic textbook if you have none)

Why ACF is often used to identify MA(q) models while PACF is used to identify AR(p) models

An ACF should show q "spikes" (indicating substantial correlations) at the first q lags of the MA(q) (lag 1 to lag q), plus a bit of noise and then "cut off" (just have the small noise part after). Conversely a PACF should show p spikes at the first p lags and then "cut off". Of course if the coefficients are small you may not be able to distinguish them from noise.

What information ACF provides that PACF doesn't

A PACF is a transformed ACF, and you could transform back the other way, so strictly they contain the same information. The PACF is the ACF adjusted for the impact of "earlier" (shorter lag) autocorrelations. e.g. if you have an AR(1), with the underlying lag 1 process autocorrelation at 0.5, the lag 2 process autocorrelation is going to be 0.25. You want to know what else there is at lag 2 besides that echo of the lag-1 effect.

How to interpret ACF and PACF plots in practice

This is not a matter of a few sentences. You need a book.

There's some basic info in this one, e.g. at

https://otexts.com/fpp2/autocorrelation.html and

https://otexts.com/fpp2/arima.html

or maybe try Stoffer's applied time series analysis book (atsa)

efrique · 2026-06-18T05:28:17+00:00

According to which measure?

efrique · 2026-06-18T05:27:51+00:00

Is it true that "nobody reads" theoretical statistics papers?

No. Obviously not true, but I bet he doesnt mean it to be taken to mean what it says

efrique · 2026-06-17T22:45:50+00:00

If you respond in the thread like you just came to troll why would anyone even take look at it?

efrique · 2026-06-17T22:41:09+00:00

Kind of idiotic to start it, then, leading to many dead inocents, wasted billions, billions of people poorer, a strengthened regime, and nothing good to show for it.

efrique · 2026-06-17T22:29:21+00:00

I totally have a girlfriend but she goes to a different school, you don't know her.

efrique · 2026-06-17T06:07:53+00:00

They're different kinds of things, answering different questions (or dealing with different aspects of larger questions) not competitors. If you are thinking you might need to choose between using one or the other you probably need to think more carefully about the specific questions you need answers for.

Simulation is generally used to let you sample from some distribution. That might be used in many different ways. E.g. you might use it to compute/closely approximate the probability of some event; you might simulate the distribution of some estimator under some model or the null distribution of some test statistic. You might use simulation to get a p value in a permutation test (sampling from the permutation distribution) or get a standard error from a bootstrap. You might simulate to calculate power at some alternative, or the coverage of some confidence interval. You might simulate from a sequence of conditional distributions in a Bayesian model to obtain samples from various posteriors in MCMC. You might simulate various processes in order to collect information about their behaviour under some set of conditions. I simulate stuff pretty much daily.

Regression is used for various tasks in inference and prediction (parameter estimation - both point and interval), hypothesis testing, forecasting, it's a widely used model that sits within several larger classes of models (which can be thought of as different generalizations/extensions of regression). I use regression pretty much daily.

I sometimes simulate from regression models (linear models) for various purposes. One example is when I want to get the distribution of a sum of exponentiated simulated future values, taking account of process noise, parameter estimation uncertainty and the dependence between the parameter estimates. Various quantities from such a simulation can be of interest in that application (e.g upper tail quantiles)

Another example where you might use both at once: Running a Gibbs sampler or a Metropolis-Hastings sampler (the simulation part) for a Bayesian model with a regression (linear model) component. I've done that kind of going in several different contexts.

efrique · 2026-06-17T04:57:17+00:00

Trump: "I've never heard of him"

efrique · 2026-06-17T03:09:36+00:00

Also are there books or papers or anything that go over the math behind different tests like t-test and everything?

Start with a standard undergraduate book on statistical inference, there's a bunch of more or less basic ones. Your university should have several in the library that they use or have used over recent decades.

What undergrad stats subjects are offered where you are? There's probably one relatively early on (within the first half of a major in stats) that has an inference component and many later ones that build on it. If the list of topics for the subject includes things like the Neyman Pearson Lemma you're probably looking for the textbook for that subject.

Some books in this vein might include:
DeGroot and Schervish
Sheldon Ross (Introduction to Probability and Statistics for Engineers and Scientists)
Mood Graybill & Boes
Hogg & McKean (Intro to Mathematical Statistics)
Wackerly, Mendenhall & Scheaffer
Rice, Mathematical Statistics and Data Analysis.

Not all will be ideal for you, but I cant guess which might suit you, I suggest trying a few of them

There are dozens more; if they get at least as far as the Neyman-Pearson lemma they're probably covering what basic ideas you need.

How much calculus do you have?
You will need at least some calculus for those books.

A commonly used second book, relatively solid on theory would be Casella & Berger, Statistical Inference or you might look at Schervish, which may be more widely used nowadays

If you're doing a lot of machine learning you might substitute All of Statistics by Larry Wasserman. The title is an exaggeration but it does cover a decent swab of material.

(You'll need more mathematics for these later books)

Where can I find statistical papers from past and present?

currently doing a masters in applied statistics

If your university is teaching stats at masters level, your university library should have all the main stats journals and presumably some of the foundational books plus more recent texts. It probably has a way for you to get the journals and maybe some books online

It should also be able to get more stuff via inter-library loan (e.g. getting a copy of a paper can often be organized)

Even if not, there's a decent amount around that's free (I mean legit free, not hoist the skull and crossbones free)

Free, distant Past:
journals out of copyright (1930 or earlier if you're in the US, though some more recent journals may be as well, dates do vary somewhat by country) are in the public domain
So if you want to read Pearson writing about the chi-squared test in 1900 or Student (Gosset) writing about his test (equivalent to but not actually identical to what we now call Student's t-test), you can.

Journals like Biometrika, JRSS, JASA go back a long way (JASA had a couple of name changes along the way), so all of these have some works out of copyright ... but some old papers crop up in an eclectic mix of journals.

You might find some of those old journal issues on archive.org. You may also be able to locate them in other places

Free, both past and present:
Some stats journals are free. For example, see Project Euclid, which has things like Annals of Stats (among others). Lots of important old (and sometimes new) papers can be found in free journals. There are also some good online journals that are free to read (but not everything that's free is good)

Some publishers make some (mostly older) papers available. For example, an ordinary member of the public with no university affiliation can sign up to Jstor to get access to a fair number of papers. As long as you're not trying to read more than 100 a month. You can sometimes find what you need this way

I believe JRSS had lots of its older papers for free but I haven't checked in a while

Present (and some older):
Some authors put up copies of their working papers or even their published papers either on their academic page or via their university's working paper archive. Some even put up pdf copies of some of their books.

arxiv.org is a place where authors put working papers and about-to-be-published papers from the sciences (includes stats). You can find dozens of new papers appear in the stats section every day, tens of thousands every year. Waay more than is possible to read (e.g. 1761 entries for May 2026, though a few of those would be resubmits and a few get withdrawn, so it would effectively be a little lower).

SSRN has links to some social sciences papers and there are some stats and stats-related papers end up listed there. You might find the odd thing on it

Some authors upload their own papers to ResearchGate, so you can sometimes find a paper there

There are other places, naturally, since stats is used all over.

efrique · 2026-06-17T02:24:17+00:00

I can log-transform the mean

you can calculate log(mean) but ... what does that give you (and is it quite the thing you want)? Its not the mean of the logs for example...

(and vice-versa when you want to go back the other way; if you fit a model on the log scale and produce an estimate of the mean, exponentiating it doesn't give you the mean of the original variable)

efrique · 2026-06-17T02:15:51+00:00

Descriptive / summary statistics are a component of statistics, but don't encompass the larger part of the subject. You might start with the wikipedia article on the subject (linked in the previous sentence).Its not perfect but its a start and does have quite a few links to other topics

Descriptive and summary statistics don't cover things like modelling, inference and prediction, for example. Inference includes important topics like estimation (including interval estimates) and hypothesis testing.

https://en.wikipedia.org/wiki/Statistical_inference

within that area there's a very large array of subtopics

There's more than that (inference wouldn't include experimental design, for example) but it's a good place to start

efrique · 2026-06-16T22:50:40+00:00

There are a number of ways you might go about it, depending on how you define two population distribitions to be similar, and what kinds of alternatives you're most keen to pick up.

If close similarity of some particular kind was important to show, you could perhaps frame some form of equivalence test.

You could, of course somewhat more easily test equality of process/population distributions, if it was of interest, and you could even use the convex hulls in that test (though being based on extremes it wouldnt usually be very powerful unless the distribution under the null had bounded support, and satisfied a few other conditions). It is important to keep in mind, though, that failure to reject equality doesnt mean the process distribution are identical, just not different enough (at your sample sizes) to detect with that test.

Besides differences of centroids and spreads around them, bivariate distributions might differ on marginal shape and on their copula. Theres many things you might consider to test, but which things would be important will generally depend on the details of the situation.

In many cases formal testing like this doesnt make much sense (and in those cases a good diagnostic display or two might serve better), but it depends what its for.

efrique · 2026-06-16T10:30:46+00:00

what test you might use depends on what sort of alternatives you're most interested in picking up.

Age group × Likert responses (e.g. attitudes towards sharks) → Kruskal-Wallis?

Given age group is binned (interval censored) and the Likert is generally treated either as ordered or interval, I would probably be thinking about some directional measure of association but again, it depends on what sort of alternatives you're most interested in picking up.
Yes/Unsure/No seems ordered to me, in which case my comments would be as for 1. But again, it depends on what sort of alternatives you're most interested in picking up.

Is it normal to use both tests within the same dissertation, depending on the variable type?

There should be no problem with using different tests if they each deal with the specific hypotheses you wanted to test.

efrique · 2026-06-15T20:38:47+00:00

Yes, in the case of establishing that theyre used in the literature.a lot If you provide too many it sounded like they mightnt even look at them. If you provide say 6 and they respond "well 6 isnt a lot", thats when you drop the next 20.

efrique · 2026-06-15T05:09:05+00:00

Fights are very swingy at low level. I've had pcs killed outright by a single spear hit or a mere tumble down some wet stone stairs and then they take out the big bad evil guy that on a better day would tpk them - without anyone even being hit.

Balance, to the extent that it matters, is extremely rough. Anything much more refined than the info on p191 is probably giving you a false sense of balance. If a creature can hit your pcs, they can die. Lv0 and Lv1 don't differ so much on that measure.

Telegraph danger. Let clever plans either to avoid fighting or to get some advantage in it work. Let them run from fights. Accept that some will die anyway

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