The question is excellent. If two independent random variable with different pdf's are multiplied together, the mathematics of calculating the resultant distribution can be complex. So, I would prefer to use Monte-Carlo simulation to calculate the resultant distribution. Generally, I use the Matlab program. If this is not a satisfactory answer, it would be good to repost your question.
Information is not sufficient to find mean deviation and standard deviation.
Standard deviation is the square root of the variance.
Standard deviation is a statistical concept and not applicable to concrete.
we calculate standard deviation to find the avg of the difference of all values from mean.,
Standard deviation can be greater than the mean.
There doesn't exist such a thing. What does exist are standardized variables, which are variables with mean = 0 and standard deviation = 1
Square each standard deviation individually to get each variance. Add the variances, divide by the number of variances and then take the square root of that sum. ---------------------------- No, independent linear variables work like this: If X and Y are any two random variables, then mX+Y = mX + mY If X and Y are independent random variables, then s2X+Y = s2X + s2Y
It is not called anything special, just 2 standard deviations or 3 sd.
The Bank, itself does not have a standard deviation. The number of branches, the number of customers, lending, profits, CEO's pay are all variables which will have standard deviations but none of them are mentioned. It is not possible to guess which one you are interested in!
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The standard deviation is the standard deviation! Its calculation requires no assumption.
Yes, to approximately standard normal.If the random variable X is approximately normal with mean m and standard deviation s, then(X - m)/sis approximately standard normal.
The standard deviation of the population. the standard deviation of the population.
If X and Y are independent Gaussian random variables with mean 0 and standard deviation sigma, then sqrt(X^2 + Y^2) has a Rayleigh distribution with parameter sigma.
The standard deviation is 0.
Information is not sufficient to find mean deviation and standard deviation.
Standard deviation is the square root of the variance.