If $f\colon X\rightarrow Y$ is a closed map of top. spaces and $U\subset X$ then is $\overline{f(U)}=f(\overline{U})$? I guess this is probably obvious?
Suppose that A and B are nxn matrices with A row equivalent to B. Prove that if A is nonsingular, then B is row equivalent to In.
I answered this on a test and it seemed right to me, but got zero credit. What did I do wrong? Was my logic incorrect?
my answer:
By definition, row equivalence me...
How do I know if I should perform a proof by induction? The problem is to prove $j < k$ if $nj < nk$ in $\mathbb{N}$ (using only the definitions of multipication, addition, ordering, etc.) but I'm told induction doesn't help even though induction was used to prove $k = j$ if $nk = nj$
@Studentmath $P(|X|\geq t z) \leq \frac{E(X^2)}{t^2z^2}$ but that doesn't get me any closer to $P(|X|\geq t z) \geq (1-t)z^2$ at least in any way i can see
I've also got Markov's inequality, $P(|X|\geq tz)\leq \frac{E(|X|)}{tz}$ but again doesn't go the right way
hint is to use Cauchy Schwarz but I have no idea how
$0<t<1$ so $0<(1-t)z^2<z^2$. If we could make $z^2\leq P(|X|> zt)$ we'd be in business. We know that $P(|X|\geq zt)\leq \frac{E(X^2)}{z^2t^2}=\frac{1}{z^2t^2}$.
@Studentmath i mean making a sequence $X_n\rightarrow X$ of simple random variables and using $E(X_n)\rightarrow E(X)$. since each $X_n$ is simple it's $X_n=\sum_{m=1}^Mc_m1_{A_m}$ for $A_m$ in the $\sigma$-algebra, so $$E(X_n)=E(\sum_{m=1}^Mc_m1_{A_m})=\sum_{m=1}^ME(c_m1_{A_m})=\sum_{m=1}^Mc_mP(A_m)$$
In mathematics, the second moment method is a technique used in probability theory and analysis to show that a random variable has positive probability of being positive. More generally, the "moment method" consists of bounding the probability that a random variable fluctuates far from its mean, by using its moments.
The method is often quantitative, in that one can often deduce a lower bound on the probability that the random variable is larger than some constant times its expectation. The method involves comparing the second moment of random variables to the square of the first moment.
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@Ted it's just because of this seminar paper :P I got familliar with lots of inequalities. But I have no clue when it comes to sigma-algebra and measure theory definitions.
@Studentmath i have never taken measure theory. The sigma algebra stuff makes sense to me when it works... just not the counterexamples when things don't work
@Studentmath Well he gave Cauchy-Schwarz as a hint so I assume that anything we find can possibly be reduced to that
I know the frustruation. Ask @Ted how I grumble at every exercise here.. Sure you will figure it out. Off with the dog, if by the time I get back you are still on it, will try to see how I can help
Hi how to ask a specific question to specific person that I know? I mean I know his name here, but when I open his profile I can't see any contact detail, such as email, skype, ... etc is there any way to contact a member here?