emphasis and time spent is definitely up to the instructor. i'd imagine div, grad, curl and 'integrating things over other things' including some form of greens and stokes theorem would be covered.
@schn Of course I know it can be proved. You asked, I thought, if it is the definition. Hence my answer.
@SillyGoose There are lots of crummy calc 3 classes that don’t cover what they should. There often isn’t enough time. Some schools have a calc 4 for that reason.
@monoidaltransform First, PRINCIPAL!! Projecting the smooth map onto the second factor is smooth.
@TedShifrin Okay, so if $\pi_{G}$ is projection onto second factor, then why is $\pi_{G}\circ \psi^{-1}$ smooth? That would be the case if I know $\psi^{-1}$ to be smooth
Compute
$$\int_0^\infty\sin(x^2)\ dx,\ \int_0^\infty\cos(x^2)\ dx$$
using contour integral.
I chose the contour integral over a sector cornered at $0,R$ and $Re^{i\pi/4}$. Let $f(z) = e^{iz^2}$ which is entire. Then,
$$\int_0^R e^{ix^2}\ dx+\int_0^{\pi/4}e^{iR^2e^{2i\theta}}\ d\theta -\int_0^R ...
suppose $X~f$ and $Y~g$ where $f,g$ are two arbitrary distributions and $X|Y ~ N(0,1)$. Can we deduce anything about the distribution $X-Y$? Intuitively I think $X-Y ~ N(0,1)$ but I don't know how to prove it.
I am studing for exams and am stuck on this problem.
Suppose $f$ is an entire function s.t. $f(z) =f(z+1)$ and $|f(z)| < e^{|z|}$.
Show $f$ is constant.
I've deduced so far that:
a) $f$ is bounded on every horizontal strip
b) for every bounded horizontal strip of length greater than 1 a ...
Let me try: Let $0<\epsilon<1$. Then
Claim: If $f$ is entire with $f(z) =f(z+1)$ such that
$$|f(z)|\leq e^{\epsilon|z|},$$
then $f$ is constant.
$(\because)$ Since $f$ is $1$-periodc, $g(z) = f\left({\log z\over 2\pi i}\right)$ is a well-defined holomorphic function except for the origin regardle...
If you want to find out the equation of a line tangent to a curve passing through a point, do you need the point slope form or the formula for a tangent line or can you use $f(x) = mx + k$ in some way?
>$f(x) = 4 - 0.25x^2$, find the equation of the tangent passing through $P(0|5)$ for example
Using $t(x) = mx + k$, you can get $t(x) = -0.5ax + 5$, but after that, can you do anything?
Hi folks, let X be a normally distributed random variable, X ~ N(0, s). I know that the powers of X: X^2, x^3, x^4 and so on aren't normally distributed, but can't derive a generic proof for that. How to do that?
$$\eta(s) = \sum_{n = 1}^{\infty} \frac{(-1)^{n-1}}{n^s} = \bigl( 1 - 2^{1-s}\bigr)\zeta(s)$$ By Leibniz, $\eta(\sigma) > 0$ for $0 < \sigma$, and since $1 - 2^{1-\sigma} < 0$ for $0 < \sigma < 1$, the result follows. — Daniel FischerJan 16, 2017 at 16:54
Why does Leibniz tell $\eta(\sigma)>0$ for $0<\sigma$?
Set $f=\sum_{i=1}^n a_i \chi_{a_i}$ and to get rid of $\int 1 dc=\infty$, define $g= \chi_{A_n}$, where $A_n= \{a_1,...,a_n\}$. And Holder's inequality on $\int fg$ gives the result :-).
They defined span as this $$ \left\langle\mathbf{v}_1, \mathbf{v}_2, \ldots, \mathbf{v}_k\right\rangle:=\left\{\sum_{i=1}^k c_i \mathbf{v}_i \mid c_1, c_2, \ldots, c_k \in \mathbb{R}\right\} $$
Suppose that $(X, S, \mu)$ is a measure space and that $f_n:X\to \mathbb R$ is a sequence of functions converging pointwise to $f$ in $L^\infty(\mu)$. It is given that $\mu(X)<\infty$. Then, I want to prove that $f_n\to f$ in $L^p(\mu)$ for any $p\in [1,\infty)$.
Remark: This problem has an addi...
X_i are iid random variables with expected value m, |m| < inf. g(x) = x^5. By the weak law of large numbers we know that mean(x) - m converges in probability 0
by applying continuous mapping theorem we can state that g(mean(x) - m) = (mean(x) - m)^5 converges in probability to 0
now I got sqrt(n) * g(mean(x) - m), where does that converge?
the first term goes to inf while the second to 0 in probability Do I need to consider which one goes faster?
I have a question about a proof in Spivak's Calculus, see a quote of the proof here. My question is about the sentence:
> Similarly, $b$ is an upper bound for $A$ and, in fact, there is a $\delta > 0$ such that all points $x$ satisfying $b-\delta < x \le b$ are upper bounds for $A$; this also follows from Problem 6-16, since $f(b) > 0$.
I am confused about the interval $b-\delta < x \le b$. When I look at problem 6-16 (6-15 in the third edition I think), it states that if $f(x)$ is right-hand continuous at $a$ and $f(a) > 0$, then there is a number $\delta>0$ such that $f(x)>0$ for all $x$ satisfying $0\leq x-a < \delta$. Shouldn't then the interval be $0\leq x-b < \delta$ in the above quote?
You could try this exercise: If f is a real valued continuous function on [a,b], a<b, and f(b) is non zero, then there exists an r>0 such that (b-r, b] is a subset of [a,b] such that sign of f on (b-r,b] is same as that of f(b).
@Koro thanks for the reply. If f is continuous at b then given $\epsilon > 0$ there exists a $\delta > 0$ such that if $|b - x| < \delta$ then $|f (b) - f (x)| < \epsilon$. How does $b-\delta < x \le b$ follow from that definition?
Continuity at end points is defined such that x does not go outside the interval [a,b]. So continuity at b means 'left continuity' and that at a means 'right continuity'.