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Will the variance of the difference of two independent normally distributed random variables be equal to the SUM of the variances of the two distributions?
Yes it is. That is actually true for all random vars, assuming the covariance of the two random vars is zero (they are uncorrelated).
How to add standard deviations?
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
Why are important in random variables?
It might help if you specified why WHAT was important in random variables.
What are the types of variables in statistics?
dependent variables, independent variable, nominal, ordinal, interval, ratio variableThere are three main kinds:Nominal: such as colour of eyes, or gender, or species of animal. With nominal variables there is no intrinsic sense in which one category can be said to be "more" than another.Ordinal: Such as Small/Medium/Large, orStrongly Disagree/Disagree/Indifferent/Agree/Srongly Agree. The categories can be ordered but the differences between pairs is not comparable. For example, it is not really possible to say that the difference betwen Strongly disagree and disagree is the same as (or double or half or whatever) the difference between indifferent and agree.Interval: These are variables where the distance between one pair of values (their interval) can be related to the distance between another pair. Such variables can be subdivided into discrete and continuous.Another way of classifying variables is independent and dependent.The dependent variable is a random variable but the independent variable can be random or non-random.
What is the difference between a random variable and random process?
A random process is a sequence of random variables defined over a period of time.
