I’m not gonna lie, I’ve been using bit.ly and goo.gl for a while.
But they haven’t made any significant improvement since shortening an URL, and I’m not saying they didn’t make new features or fix things to share this URLs in a more easy way.
But, is this everything?
I blog about this on my medium post, so if you want to read my whole explanation and how we can improve it: https://medium.com/@idgm/are-short-urls-outdated-85fd26913624
So I’ve been dipping my toes into p-adic numbers (Mostly 10-adic, if my understanding is correct). But I was wondering what …99999 is equal to.
Is it equal to 1, similar to how 0.9999…=1 in decimal?
Is it equal to zero due to “overflow”?
Or is it just its own thing that isn’t equal to anything else.
Additionally if anyone has any good resources for p-adic numbers, I would love to delve much deeper. Thanks!
I’m trying to model the effect of drug A in terms of dependence on drug B. Lets say A is cannabis and B is heroin. First I created a DAG, with:
MJ use > tendency to use drugs > Heroin use > heroin dependence
I had a number of covariates (education, income, sex, etc) feeding into ‘tendency to use drugs’ but the main issue is the complex relationships imply bidirectionality.
- alcohol use > tendency to use drugs > MJ use (here the relationship goes BACKWARDS)
- income > drug tendency, mental health > drug tendency (but income and MH also feed into each other)
All the examples I’ve found seem to be unrealistically one-directional (such as warming up on ingame injury). I’ve though about path analysis and SEM, but again, all the examples seem to inexplicably contain only unidirectional relationships. Since DAG/SEM is used in social sciences often, I’m confused how researchers consistently have unidirectional relationships. Am I missing something fundamental here?
You can see an example DAG here: dagitty.net/mIqMh3b
So i was wondering what would be the various methods to know the surface area of a peeled banana. One method i was told of was plotting 2 graphs on graphic calculators and by using integration, finding the surface area of the banana. Anyone has any ideas how to go about it?
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I got the widely-suggested book ‘An Introduction to Statistical Learning’ and am going through it right now. I’d like to spend a bit more time learning the theory behind linear modeling since the book didn’t dive too in-depth. Stuff like t-statistics about Nevin Manimala, p-value, and whatnot.
I’m going through Coursera’s Linear Regression Model course as well but it’s really really cursory and not entirely useful IMO. It hasn’t mentioned anything aside from R2 in the first week’s worth of lessons…
So I’m looking for resources (books, pdfs, online classes, etc) that teach the theory a bit more but not at a grad-school level…
Joined my father on picking up his 991.2 GT3 touring at the Porsche factory in Stuttgart and promptly spent the rest of the day driving through the Black Forest.
First off I love the gearbox on this thing. Coming from the Shelby’s tremec 5050 the shifter just feels so damn smooth. If I had to sum it up in one word you arn’t shifting the GT3’s gears merely gliding between them. The clutch is nice and soft with a forgiving catch point compared to my GT350 and in bumper to bumper traffic was a breeze. However the car seemed a bit unhappy if trying to slam through the gears but this might just be my bad timing / getting used to the car.
Second worth mentioning the interior. I love how simplistic it is with the most important part being NO BUTTONS ON THE DAMN STEERING WHEEL. Maybe 6-7 buttons on the center console and a couple of switches mated to Porsche’s corporate Infotainment is meh (Shoutout CarPlay). He optioned the 18 way leather and cloth seats and are quite comfy after 3 hours straight in them. All in all a relatively compact interior with nothing really key missing.
Lastly the engine. It’s still in break in and will Rn for a bit (Porsche is saying keep it under 5k rpm for first 1.5k miles) but man it really wants to run once you get it around 4K, it’s intoxicating and that’s coming from a Voodoo driver with plenty of power even short shifting. The PCCB brakes are a beaut and I have no complaints.
If I had to pick one thing to gripe about it would be the overly stiff steering even in normal mode. Think Tesla Model S in stiff mode bad. Things get better with speed but sub 40 kph its highly annoying.
If anyone has any questions or things they want me to answer lemme know as we got the car for about 3-4 days before it gets shipped back to the states. All in All I’m seriously blown away with how easy this car is to drive.