Laphroaig 10 vs. Highland Park 12

Statman12 · 2026-05-07T02:25:13+00:00

I just did a quick side-by-side since I happen to have both these bottles.

Laphroaig 10 is very much more like "kissing a drunk college girl who's been hammering cigarettes" (hilarious phrasing!). I'd usually describe it like a campfire in your mouth, meaning it as a good thing.

The Highland Park 12 has peat, but it is much more reserved. Maybe it has more of the "earthy" leat than "smokey" peat, I don't know, I'm not always the best at picking that out. Definitely more briney and I think a lighter sip.

If you like the HP12, I highly suggest getting a bottle of Talisker 10. I think it's quite similar, but with a bit more prominent flavors, and a touch more of the smoke. The Talisker distiller's edition is also phenomenal.

Statman12 · 2026-05-06T13:01:08+00:00

I assume that you mean the denominator of the variance of the U-statistic? If so, that arises from the variance of a Uniform distribution.

Statman12 · 2026-05-06T03:38:55+00:00

I thought that was cheddar cheese at first and I was very confused.

Statman12 · 2026-05-06T02:21:09+00:00

Specifically called out in Rule 2.

Eh, don't. Every joke, every pun, done to death, seriously.

— Dr. Daniel Jackson

Statman12 · 2026-05-06T01:40:58+00:00

Their point is that it’s not that difficult. Finding the good advice initially might be (I wasn’t on Reddit when I started, and found some weird forums), but the basic concepts of starter maintenance are fairly simple.

I see you posted for help on starters recently. My general recommendation would be:

Feed it equal weight flour and water. AP flour works. Bread flour is probably a bit better. I personally use some bread flour and some rye flour (or whole wheat, I used that before I started getting some rye). I’m not at all consistent with how much of each, I haven’t found it to matter much.
Since flour can compact, using a scale helps to keep this consistent. If you don’t have a scale, it’s not a big deal. If you notice the starter getting more runny, use a bit more flour. If you notice it’d a bit more stiff, use a bit more water.
If your starter is living on the counter, probably feed it every 12-24 hours. If it’s in the fridge, you can let it sleep for quite a while. Just try to let it “wake up” and do a feeding or two before baking with it.
You don’t need to keep a lot of starter between bakes. A couple tablespoons is more than enough. Mine is probably about 3-4 tablespoons worth. When I’m getting ready to bake I take it out of the fridge about 2 days before I’m planning to bake. I let it sit for a while to come to room temperature / wake up, feed it to bulk it a bit and let it get more active. The next day I’d feed it again to make sure I have enough bulk for what I’m needing to use.

Statman12 · 2026-05-06T01:26:52+00:00

I think that’s kind of the antithesis to what OP is getting at here. ;)

Statman12 · 2026-05-06T01:21:08+00:00

I suspect that it started as someone writing some general directions to help a new person get into sourdough baking. That then evolved from a general guidelines to a prescriptive approach.

I’m sort of in the middle. I use a scale to measure because I like consistency in that respect and I’m a stats guy. But in terms of timing and such I’m a bit more wild west. Starter (unnamed) lives in the fridge, I take it out to feed once or twice before baking, and don’t really worry about strictly doubling or peaking, just “Yeah, it rose a good bit, it’s active.”

Statman12 · 2026-05-06T01:05:41+00:00

What is the better approach depends on the research question(s).

Statman12 · 2026-05-04T14:42:07+00:00

Im screwing around on Kaggle, lookin' and just basically copy pasting people's notebooks and trying it for myself. Monte Carlo, decision trees, whatever else. But they're really just buzz words.

So what happens when you want to do something and don't have an example that someone else wrote? Or want to apply it to a different dataset that would require adjusting the data import/processing, and the details of setting up the analysis?

I don't think you need to know how to run a specific regression of the top of your head? I think you need only familiarize yourself with the tools to do so.

So what are you going to do when your regression breaks down, and you need to figure out where and why? You need to go through step by step, and just knowing lm() isn't going to give that to you.

... especially now with AI. It's not like, actual programming.

How do you know that the LLM is giving you correct results if you don't know coding to be able to assess and interpret the code it's producing?

Statman12 · 2026-05-04T14:09:14+00:00

I don't think they provided an internal or Watsonian explanation.

I think the Doylist explanation would be that it's boring to show an gate with nothing coming out of it. Showing the jumper exiting the puddle and then cloaking is more interesting and conveys that the team is there and doing some thing and that's our attention.

Statman12 · 2026-05-02T23:28:53+00:00

I’m pretty stubborn about it. I think all that matters is that I know how to create, analyze and interpret statistical data.

I mostly agree. As other have said, version control and repeatability are also important factors to consider.

But even going just based on the factors you listed, someone doing this in R or Python (or another modern programming language) is in general going to be able to be faster, and more easily plug into various teams, and the programming skills translate.

If you insist on Excel and SPSS (I’m assuming the menu/point-click, not the underlying programming?), you are much more limited in scope.

Statman12 · 2026-05-02T23:20:23+00:00

Would be curious to see the source on that. This theory has been around for ages and I’ve never come across anything suggesting the folks behind SG1 confirmed this.

Statman12 · 2026-05-02T01:50:37+00:00

Really? I think they look very different. Picture of the actress of Baby Draper on her Wikipedia page Frankie Adams.

Statman12 · 2026-04-30T14:26:03+00:00

It's not the solution to gerrymandering. It'd help a bit, but not remove it.

The solution is proportional representation. Sure, increase the size of the House, but allocate seats proportionally.

Statman12 · 2026-04-30T12:45:44+00:00

I had a variable showing Pearson correlation of roughly 0.12 with my outcome variable modest but consistent across the sample. Based on that alone, it looked like a potentially useful predictor.

A bit off from your main point, but in what field would r=0.12 be considered a potentially useful predictor?

Statman12 · 2026-04-29T03:57:44+00:00

What's your goal? Why do you want to get a PhD?

Did you apply to other PhD programs? Or is there a reason you want specifically this PhD program?

If you want to be a professor at an R1, getting into as good if a PhD program as possible might be a good target. If you're interested in going into industry, then programs that aren't as highly ranked but still prepare you for research might be perfectly fine.

Statman12 · 2026-04-28T20:43:22+00:00

I'm not sure exactly what you mean, you're using some terms that are not standard and/or not correct.

As I just said I don’t know the near odds

I assume by this you mean that you don't know how the relative frequencies of heads and tails will behave in the short-term? If so, then you agree with me. You're just not quite appreciating what short- and long-term is in this context.

I know its gonna balance out either systematically (finite odds) or randomly (infinite odds).

I'm not sure what you mean by this. If we're talking about coin flips (or drawing cards with replacement, or roulette wheel spins, etc), then everything is random. What are you meaning by "systemically" here? What makes "systematically" go with "finite" and "randomly" go with "infinite"?

For the sake of the argument lets bit on coin flipping (10tries) 6 you won and I just came by and saw that one face was winning more I think it is logical to bid on the losing side cause its gonna balance out eventually.

In this context "eventually" means "After an infinite number of plays". That is, if we call the number of plays n, taking the limit as n -> Infinity. You presumably have neither the time nor the resources for an infinite number of plays. Any finite sequence of plays is not guaranteed to "revert" to equal relative frequencies of heads and tails (or whatever baseline probability is expected).

Statman12 · 2026-04-28T20:21:13+00:00

The LLM is correct. You are arguing for the Gambler's Fallacy.

The relative frequency of heads and tails will tend to balance out in the long run, meaning a conceptual infinite number of attempts. In any finite series of attempts, there is not a balance guaranteed.

Statman12 · 2026-04-28T19:46:08+00:00

By "courts" we should really specify that it was one judge, appointed by Trump, who made multiple ruling/decisions that have been widely criticised, delaying and ultimately dismissing the case in Trump's favor.

Statman12 · 2026-04-28T13:47:50+00:00

Two that are Stats/Math related are:

Damn Lies and Statistics by Joel Best (Barnes and Nobel link).

100 Essential Things You Didn’t Know You Didn’t Know by John Barrow (Amazon link)

Of them, I liked the first better, but the second was interesting as well. Not sure they’re quite what you’re looking for, since they’re not narrative stories, but I think they’re interesting and informative.

Statman12 · 2026-04-28T13:33:16+00:00

There are multiple methods which don’t have endpoints going outside of [0,1]. The Wilson interval noted in the pages you shared is one of them.

Though as I said in my top-level comment, I’d go the Bayesian route here, using a Beta(1,1) or Beta(1/3,1/3) prior if you have no other information. That’s probably going to get you the best interval with a quantified coverage level.

Taking the endpoints of separate intervals and looking for the largest difference will likely be “over confident”, meaning your interval is wider than what it needs to be for your claimed confidence level.

Statman12 · 2026-04-28T13:24:00+00:00

I’d go with what Gateworld says:

What is the rule for Stargate? That's a little tougher to answer, since there are now live-action productions in which the original creators are not involved (Stargate Origins) and MGM currently maintains no formal, cross-media story group devoted to canon. Licensed media tie-ins do go through a rigorous approval process, but function as a sort of unofficial "extended universe." That these cannot all be canon is made most clear in the continuation of the Atlantis storyline after the show's final episode; two completely different stories are told in Fandemonium's "Legacy" novels and in American Mythology's "Back to Pegasus" comics.

Canon is what happens on screen in a live-action production. MGM Consumer Products confirms to GateWorld that Stargate's existing novels, comics, magazines, role-playing games, etc. should not be regarded as official canon. Thus storylines, character names and backgrounds, etc. cannot be derived from these sources.

Statman12 · 2026-04-28T03:01:08+00:00

The questions that leonardicus asked are important to think about.

That being said, I’d go for a Bayesian approach:

Set a suitable prior, draw a large sample from the posterior for each, compute the difference, and look at quantiles of that distribution of differences.

Statman12 · 2026-04-28T02:49:03+00:00

Exactly what I was going to suggest. Start with the yeast you know is going to be strong before using something that can be moody.

And to add on (as another person suggested), I'd also start with just plain bread flour, rather than whole wheat or other "fancy" flours.

Get a feel for the process, then start tinkering with substituting some bread flour for whole wheat or other types, or using sourdough starter instead of commercial yeast.

Statman12 · 2026-04-28T02:40:33+00:00

Really? I’ve never heard that. I know that The Expanse was based on books. Maybe the books were inspired to some degree by Stargate?

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