Because they reflect the average level and stability of random variables, the mean and variance of random variables have important applications in market forecasting.
Expected formula of discrete random variables: the probability that the value of discrete random variable X is X 1, X2, X3...Xn, p(X 1), p(X2), P (X3)...P (Xn) is the corresponding value of X can be understood as data X 1, X2.
Then e (x) = x1* p (x1)+x2 * * p (x2)+...+xn * * p (xn) = x1* f1(x/kloc-0
Variance formula of discrete random variables: d (x) = e {[x-e (x)] 2} = e (x 2)-(ex) 2.
Variance and expectation of normal distribution;
1, uniform distribution: the expected value is (a+b)/2, and the variance is the square of (b-a)/12.
2. Binomial distribution: the expectation is np and the variance is npq.
3. Poisson distribution: the expectation is p and the variance is p.
4. Exponential distribution: the expected value is 1/p, and the variance is1/(the square of p).
5. Normal distribution: expectation is U, variance is&; The square of.
6. If X obeys the 0- 1 distribution with the parameter p, then E(X)=p and d(X)=p( 1-p).