[Q] How to apply correlation coefficient on varying subject matter?

*Subject matter means things like cancer, finance, aircraft disaster, school examination results, etc.

I understand if the correlation values gets closer to 1, the correlation is strong. But I got varying sources saying that 0.4-0.6 is not strong, and some says it’s depending on the field; this site sums it all up; here are some excerpts:

… There is no rule for determining what size of correlation is considered strong, moderate or weak …

… For this kind of data, we generally consider correlations above 0.4 to be relatively strong; correlations between 0.2 and 0.4 are moderate, and those below 0.2 are considered weak.

…. When we are studying things that are more easily countable, we expect higher correlations. For example, with demographic data, we we generally consider correlations above 0.75 to be relatively strong …

So, I’m a bit confused:

  1. Is there a way for me to justify why in my subject matter (i.e. Banking), I’d consider 0.4 strong?
  2. Would it be reasonable due to 50% of the data clumped to 0.4, the data that are having 0.4 correlation values be considered as strongly correlated?
  3. If it’s 0.4 correlated, can I say there is 40% probability that the thing could happen?

Hope someone could help : (

*(not a statistican BTW – have some basic understanding of statistics)

submitted by /u/runnersgo
[link] [comments]

For those that daily a beater, how do you resist the urge to upgrade?

I’m currently stuck with my 94 Civic DX Coupe 5 speed as my daily driver for the foreseeable future. I intended this car to be a project car, but I ran into some unforeseen circumstances that caused it to become my daily. While it’s very fun to drive around town, it lacks all of the modern amenities like power windows, good speakers, and a/c. Plus, it’s not the most reliable right now as it won’t start in hot conditions, has a weird kind of duck sounding noise when it gets to around 3k rpm (no tach though so not exactly sure what rpm it occurs at), and the speedometer is frequently off by 20mph. Even though I could get something slightly better, it wouldn’t be the smartest choice for me as I’m still in college.

Anyways, for the rest of you that daily a beater, what keeps you from getting something even slightly better?

submitted by /u/Nightmaarez
[link] [comments]

Muffler delete on a 99 Corolla

So, bear with me. Is it logical to do a muffler delete on a Corolla from 1999 or not? Should I not do any modifications to this car or does it not matter. I’ve read a lot on the internet that this car is “sacred” and is only meant for driving and nothing else. Idk if I should do any mods so that’s why I’m asking here.

TIA.

submitted by /u/itshowitbeyunno
[link] [comments]

Approximate modulus of continuity of L^1 functions

Latex version: http://mathb.in/39439

Let f: R -> R be in L1 (loc). Define the approximate left modulus of continuity, L_f (x, e): R x R+ -> R+ union +inf as

L_f (x, e) := sup {d >= 0| 1/r Int [x-r, x] |f(t) – f(x)| <= e for all 0 <= r <= d}

Similarly define the approximate right modulus of continuity by

R_f (x, e) := sup {d >= 0| 1/r Int [x, x+r] |f(t) – f(x)| <= e for all r <= d}

Note that if f = g a.e., then L_f = L_g a.e. and R_f = R_g a.e., by which we mean for almost all x, for all e, L_f (x, e) = R_f (x, e).

Do L_f and R_f determine f almost uniquely almost everywhere? In the following sense:

Question: Suppose f and g in L1 (loc) are such that L_f = L_g a.e. and R_f = R_g a.e. Does it follow that f = g + c a.e. or f = g – c a.e. for some a.e. constant function c?

submitted by /u/penberbromster
[link] [comments]

If this is the final year of the EJ257, aka 2020 Subaru WRX STI (US), do you think a low mileage example will command a premium in 10 years?

I got into a bit of a debate with a few friends on the future used prices of an STI.

If internet sources hold true and the WRX STI gets the fa in the 2.0 or 2.4 variant and the infamous EJ goes away, do you think it will have any kind of value in the future?

Granted it’ll have a manual transmission so that in itself will be rare, but I was curious what the car community would think, as if it may command a similar resale value to the EVO…

submitted by /u/Depressed_White_Male
[link] [comments]

Prospective Math, Physics, or CS Major – Opinions for College Class Schedule?

So I’m starting my 4th semester in college, still undecided on what exactly I want to major in. I’ve narrowed it down between math, physics, and computer science. I’d love a combination of the 3 by double majoring in 2 and minoring in the other. I’m still in a position that I have time to take courses from each department to get a feel of each subject. I’m posting on here because I’d love to get some insight as to which courses I should take and which I should drop. I’m primarily interested in applied math grad school, but I might rather do physics or CS which is why I’m trying to see which one I more naturally gravitate towards so I can double major.

I’m currently enrolled in:

-Classical Mechanics

-Linear Algebra

-Theory of Computation

-Algorithms

-Complex Variables and Applications (about 50% proofs, 50% computational)

-Basic Real Analysis (big emphasis on proofs – not the advanced Real Analysis, to clarify)

I wish so badly I could take them all, but I need to drop one to avoid overworking myself and failing at everything (even 5 seems scary.. we’ll see how I feel by the drop deadline about actually taking 5).

I have to stay in Classical if I want to minor or major in physics because I’d be behind otherwise. I want to stay in linear algebra because I feel ignorant having not taken it yet.. I just think it’s such a core part of the undergrad math curriculum, I don’t want to wait any longer. Algorithms is probably one of the most useful CS courses – I refuse to graduate without it, and I have friends taking it this semester so it’s probably the best time to take it to get a good grade. Basic Real Analysis seems essential since it will be my first real rigorous proofs course, though I could take it over the summer (though 1 month seems like a rush to develop this way of thinking and see if I like it enough to pursue math). Theory of Computation could wait. Not sure how immediately useful it is. I think it’d be great exposure to the field of theoretical CS, though. It does involve proofs. Complex Analysis seems to be a requirement for all applied math grad schools. I know I’d take it at some point regardless, as it is used in physics. The only reason I wouldn’t take it this semester is because my professor is hard to follow. I think I’m either going to drop complex or theory of comp, though I’m still considering dropping basic real.

I’m just generally curious to hear what people’s thoughts are. If you’re in physics, applied math, or CS, which combination do you think would likely give me adequate exposure to each field so hopefully I’ll know what I’m most interested in by the end of the semester?

I’m also planning to pursue research in one of the fields, though I don’t think I will actually conduct any until the summer. My hope is to at least meet with some professors, find a topic that seems interesting, do a bunch of reading this semester, etc. and go from there.

submitted by /u/dontcry2022
[link] [comments]