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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.

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Q: What is the formula for finding the standard deviation of two independent random variables multiplied together?

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Information is not sufficient to find mean deviation and standard deviation.

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.

Standard deviation is the square root of the variance.

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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 standard deviation is the standard deviation! Its calculation requires no assumption.

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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!

The standard deviation of the population. the standard deviation of the population.

The standard deviation is 0.

Information is not sufficient to find mean deviation and standard deviation.

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.

Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.

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.

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