To show $\supset$, let $x\in [f^{-1}(a),f^{-1}(b))$, i.e. $f^{-1}(a)\leq x< f^{-1}(b)$. Since $f$ is increasing, the latter inequality holds iff $a\leq f(x)<b$, which shows that $x$ belongs to $f^{-1}([a,b))$.
Now, I'm unsure if I've done this correct because I have not used continuity anywhere...this feels not right.
Upon even closer thought, what I said in my last message can't be right. A strictly monotone function needn't be continuous for it to be injective...so where in my argument, if it is correct, is continuity required? Hmm.
Hi, chat. Say you had two repeating sequences which we can write $\overline{1,2,3} := a$ and $\overline{2,1,2} := b$. What if you formed an operation on these that returns another repeating sequence. Here is one: the sum 1 + 2, and 2+1 match (from the first two entries of each respectively) so the first entry in the op output is $3$.
Then continue this way until what your doing starts to repeat itself
So the next would be 3+1 = 2+2 = 4
And teh next would be 2 + 3 = 2 + 2 + 2 = 5 and so on...
I mean 2 + 3 = 2 + 1 + 2 etc
Have you seen this operation before?
And how do we determine if it can terminate early? Meaning we already have determined the part that is going to repeat, without filling out $\text{LCM}(|a|, |b|)$ entries?
Believe it or not such operation's output values if you could somehow bound them by certain formulas has applications to NT problems.
This is about repeating sequences of natural numbers such as $\overline{6} = 6,6,6, \dots$ or $\overline{2,1,2} = 2,1,2,2,1,2, \dots$. I am aware that these can be faithfully represented as the sequence of coefficients of a power series $f(x)(1 + x^k + x^{2k} + \dots)$ where $k = \deg f + 1$. ...
Is it possible for S4 to act on itself so that the orbits have length 1,3,4,4,4,4,4 ? @Thorgott do you have any idea for this question? Conjugation gets us 1,3,6,6,8
I'm new to this and I'm not looking for big explanations (although I've tried to google the heck out of this, and yet I haven't been so successful). I'm wondering what the difference between a continuous and an absolutely continuous cumulative distribution function is?
In my textbook, the author simply says "In this book we are only concerned with two kinds: discrete distributions and (absolutely) continuous distributions." The author clearly has more to say, but unfortunately doesn't. If anyone could shed some light on what the difference is, I'd be grateful.
@Balarka daily fact (this one I can prove): given an element $\alpha\in\pi_{2n-1}(S^n)$ and $\beta_1,\beta_2\in\pi_n(X)$, we have $(\beta_1+\beta_2)\circ\alpha=\beta_1\circ\alpha+\beta_2\circ\alpha+H(\alpha)[\beta_1,\beta_2]$, where $H$ is the Hopf invariant and $[-,-]$ the Whitehead product. the Hopf invariant measures the failure of additivity of pulling back along the map in terms of the Whitehead product.
@psie Absolutely continuous means there exists a pdf. That is, a function $f(x)$ such that $P(X\in A) = \int_A f(x)dx$. If its merely continuous, then such pdf doesn't have to exist. We are only guaranteed that $t\mapsto P(X\leq t)$ is a continuous function.
The counter-part to absolutely continuous random variables are singular continuous random variables, for which there exists a Lebesgue measurable set $\Omega_0$ such that $P(X\in \Omega_0) = 1$ but $\lambda(\Omega_0) = 0$ where $\lambda$ is the Lebesgue measure
But nonetheless, $t\mapsto P(X\leq t)$ is still continuous
Every random variables decomposes into discrete, absolutely continuous, and singular continuous part
an example of a singular continuous random variable is the one whose CDF is based on the Cantor's devil staircase
In mathematics, the Cantor function is an example of a function that is continuous, but not absolutely continuous. It is a notorious counterexample in analysis, because it challenges naive intuitions about continuity, derivative, and measure. Though it is continuous everywhere and has zero derivative almost everywhere, its value still goes from 0 to 1 as its argument reaches from 0 to 1. Thus, in one sense the function seems very much like a constant one which cannot grow, and in another, it does indeed monotonically grow.
It is also called the Cantor ternary function, the Lebesgue functio...
extended from $[0, 1]$ to the whole real line by setting $F(t) = 0$ for $t\leq 0$ and $F(t) = 1$ for $t\geq 1$
You should treat singular continuous random variables as the leftover part which no one really cares about
@Jakobian does it need to be $1$ in $P(X\in \Omega_0) = 1$ or could it just be any other number in $(0,1)$? That would be the negation of absolutely continuous measure, right?
Also compare for the notion of absolute continuity of measures $\mu_0 < < \mu_1$ and singularity of measures $\mu_0\perp\mu_1$. Above names boil down to those concepts for the law of random variable $X$ and the Lebesgue measure.
@Jakobian You lost me after the second syllable in your reply, but I love your enthusiasm and admire your math skills :) I'll migrate the post :) Thanks!
@Jakobian yeah, I'm not really sure what I was talking about :) but what did you mean by "counter-part" to AC random variables? I interpreted "counter-part" as the "opposite", so that's why I thought, well, the opposite of AC, according the definition below, must be that there exists a $\Omega_0$ such that $\lambda(\Omega_0) = 0$ but $P(X\in \Omega_0) = 1\in (0,1]$ (since it's an implication)
the negation would be that the measure that is dominated just needs to be nonzero (like you negate, say, uniform continuity)
I have a typo above. I meant $P(X\in \Omega_0) \in (0,1]$.
The problem was to find the first integral of a PDE. I got a characteristic system (t is the parameter) and then by applying some functions and operations I got to the above equation. Basically the system is linear and homogeneous
$M_{m*n}(\mathbb{R})$ $A\subseteq M_{m*n}(\mathbb{R})$ $A=\{a_{ij},1<i<m \land 1<j<n\}$ $W=\{A:a_{ij}=a_{ji} , \forall i\neq j\}$ Prove that A is a subspace of M, pls help
Just want to double check something. If a function is continuous, then $X$ connected implies $f(X)$ is connected. The contrapositive of this must be; if $X$ is connected but $f(X)$ isn't, then $f$ isn't continuous. Is this right? The reason I'm asking is because this is a claim made here.
i would push back a little on "the" contrapositive and "must be". one always has some choice as to how you phrase logically equivalent things in english, if not also in symbols. whatever uniqueness there is, is not as strict as you might expect.
so here, e.g., if your P is "f: X to Y is continuous and X is connected" and your Q is "f(X) is connected," one way of phrasing the contrapositive of P => Q is "if f(X) is not connected, then either f: X to Y is not continuous, or X is not connected"
and maybe you're unconsciously using even further logical rewrites to add in "okay, so if f(X) is not connected and X is connected, then f: X to Y is not continuous." logic books will give interesting latin names to what is going on here.
so, it is a logically sound thing to say, and it comes from "if X is connected then f(X) is connected," but i don't know that there is a machine where if you fed in that sentence and pressed one button labeled "contrapositive," that it would spit out what that comment is using.
@leslietownes hmm, interesting, so would you say the claim in the link is correct? The answerer says that the inverse of $f:(-1,0]\cup[1,2]\to[0,4]$ given by $x\mapsto x^2$ is not continuous because $[0,4]$ is connected but $(-1,0]\cup[1,2]$ isn't...
I guess the claim is correct, rereading your version of the contrapositive :)
i.e. "if f(X) is not connected, then either f: X to Y is not continuous, or X is not connected"
yes, it is correct. i am not sure i would choose that way of explaining that example to a classroom full of people who have just learned about continuity, but it's fine
e.g. the last time i taught real analysis, students first encountered continuity as a pointwise condition that was only later extended to sets, and connectedness came a few pages later than continuity in the textbook. in that kind of setting i might first "point" out (ha ha) that the function f^{-1} is not continuous at 1 in that example.
but that way of looking at it is a good one, because it shows that you don't need to engage with the specifics of what f^{-1} is, or where its discontinuities might be in some example, at all.
one thing you might be wrestling with is that often a theorem is stated as list of hypotheses or even just a narrative story that sets a context, followed by "if P then Q," where the context is not explicitly part of the "if-then" statement.
and there's the question if, if you want to symbologize it, whether you symbologize just the P and Q, or if you also take the story and symbologize that and add it with an "and" to the P, or do something else logically equivalent with it.
and different people and textbooks will resolve that in different ways, depending on context. i don't think there's one machine way that does it, any more than there's one way in english of saying the underlying logical content.
in "intro to proof" books they would often symbologize something like "Let a and b be integers. If a and b are even, then a+b is even" such that the contrapositive is just "if a+b is not even, then either a is not even or b is not even," and not take the hypothesis about a and b being integers and shoehorn that into the statement, to arrive at something like "if a + b is not even, then not (a is even and b is even) or not(a and b are integers)."
maybe something similar is going on here. as you've stated the theorem in English, it's "about" continuous functions, and it feels weird to turn it into something that might also be "about" functions that are not continuous. even though logically it is also about that.
all of those expository choices seem to affect mainly which pieces of your setting get explicit expression in symbols and which don't, i.e., they are about symbolic formalism and not what the meaning is. and they are genuine choices, not just the output of a mapping that takes in English and spits out The One True Formalism.
@psie I wouldn't phrase it that way. The theorem really should be read "If $f$ is continuous and the image of $X$ is connected, then $X$ is connected."
The contrapositive is then "If $Y$ is the image of a function $f$ and $Y$ is disconnected, then either $f$ is not continuous, or $X$ is not connected."
oh, they edited their post to make it less an illustration of what i was talking about. the title was "Can someone explain this to me? I for the life of me cannot understand this" and the post was "if X, then X" where X was the exact same symbolic expression.
of course it was a typo and they fixed it, but it illustrates my point better in its original state.
I don't understand. An array is usually an $m\times n$ arrangement of numbers. Does this mean that $A$ and $B$ are both simply lists of $6$ numbers?
And what is $A[i:6]$?
I suspect that you are a programmer of some sort---we are mathematicians, not programmers. You need to speak math, not C (or python, or FORTRAN, or whatever language that is).
simd: this may or may not be relevant but if A is a 6x1 "column vector" and B is a 6x1 "column vector" with entries (b_1,b_2,b_3,b_4,b_5,b_6), then the columns of the 6x6 matrix A B^T are, in order, A scaled by b_1, then A scaled by b_2, then A scaled by b_3, and so on. i.e. the columns of this 6x6 matrix product encode the results of scaling the vector A by each one of the entries of B, in order
i'm now silently wondering about "length 6" and "indexing from 0" and the whether the 6 in "i:6" (whatever that is) should be a 5
Does Von Neumann's Minimax Theorem apply to zero-sum games only if they consist of a single move made by each player, or also in zero-sum games with several alternating moves? If the latter, then why does it not imply that in Chess neither white nor black has an edge? If the former, then why does it appear when players use multiplicative weights to play zero-sum games over a sequence of days (Example: youtube.com/watch?v=-_pIUD5Jzl0)?
i do like that it's not hard to sample from the Cantor distribution. (or, at least, it's not hard to sample up to some precision, but that goes for the uniform distribution too)
Math is like a mass delusion. There is literally no point to it. Its not even made for anything. Sure maybe that was the purpose at the beginning. Right now? Bizzarre things NO ONE needs
@Jakobian How do you feel about ballet? opera? hip-hop? swing? oil-on-canvas? literature?
Lots of people have argued that these things are pointless and serve no purpose, yet they seem, as a group, to be rather important to human flourishing.
jakobian you should set a goofy meta mathematical goal, a kind of stunt, and try to achieve it. e.g. "publish a paper that contains some number worked out to 20 decimal places in it" in a non pay to play journal, or "publish a paper in a journal that has the funniest [to you] name that you can manage, without paying for the privilege"