Let me try to help you with a general remark, because I'm not sure what you are trying to do exactly. If you want to find some statistical property (such as the expected value, or the covariance) of a random variable, or a group of random variables, you'll need to choose between two options.
The first option is to do everything symbolically. You could characterize this approach by the fact that you never take a sample, using Statistics:-Sample or Finance:-SamplePath, or use data from the outside - it's just the use of the abstract distribution. You can for example ask for the ExpectedValue of the square of the normal distribution with parameters mu and sigma. This is almost exclusively the domain of the Statistics package - the Finance package typically requires the use of the second approach.
The second option is to use data. You can generate SamplePaths or Samples and then measure the properties of these realizations of the random variables. In this case, you'll need to make sure that for every call to a statistical property you want to compute, you have a sample of data for that call. In particular, if you want to find the covariance between, say, a property of a process at t=1 and a property of the process at t=2, then you'll need a sufficient number of replications of the sample path as a whole and pass the values at t=1 and t=2 of all sample paths to the proper function call. You can't compute the covariance by calling ExpectedValue on every data point individually.
Let us know if this helps, and if it doesn't then tell us exactly what you are trying to compute.
Hope this helps,