179,075 reputation
16121272
bio website
location
age
visits member for 3 years, 8 months
seen 14 mins ago

As somebody used to say:

Does research. Smokes. Battles administration. Smokes. Wishes he could stop battling administration so that he could have more time to do research. Smokes some more.

The same. Except I do not smoke.


How to ask a good question?

This paragraph is for my personal use but freely available:

Welcome to Math.SE! Please, consider updating your question to include what you have tried and where you are getting stuck. That way, people on this site will know exactly what help you need.


12h
answered Calculate summation of square roots
12h
answered Probability - pmf for alternating probabilities
14h
answered Prove $\int s d \mu = \sum^n_{j=1} a_j \mu(A_j)$ for $s=\sum^n_{j=1} a_j 1_{A_j}$ not a standard representation of $s$.
14h
answered Laplace transform of the autocorrelation of a wss random process
15h
answered Value of the integral $\int_0^{2\pi}\int_0^{2\pi}\delta(k_2\cdot e^{i\theta}+k_3\cdot e^{j\phi} +z )d\theta d\phi$
19h
answered How to solve $y'=\frac {e^{x-y}}{y-1}$?
23h
answered Maximum rate of change along which curve?
23h
answered I want to know whether the following is periodic or not periodic
1d
answered How to solve the complex ODE $\mu f'(x) = if(x)$ in the interval $[-\pi, \pi]$?
1d
answered Explicit CDF associated to Gamma PDF
1d
answered Solving $\log(x) = vx^α$ for $x$ via Lambert W function
1d
answered Poisson random variables and Binomial Theorem
2d
answered Proof all possible unions of a collection of sets is a sigma algebra
2d
answered Find $E[N]$, where $N = \min\{n>0: X_n = X_0\}$
2d
answered Standard Normal Distribution and CDF
2d
answered Markov Processes: $P_x$ and $E_x$
2d
answered If $p > 5$ is a prime number, then the last digit of $p^4-1$ is $0$.
2d
answered $n$-step transition probability of a Markov chain
2d
answered Comparing Squared Difference of a Random Variable and it's mean, or it's mean conditioned on a $\sigma$-field.
2d
answered The “on $\left\{ \tau <\infty \right\}$” in the Strong Markov Property