I have a spatio-temporal data set with (n,m) spatial and k temporal dimensions.
My initial analysis consisted of spatially averaging the data and looking at the time dependent behavior. This resulted in a vector of length k for the mean and standard deviations.
Now I want to average the those means, to get an overall scalar value. How do I calculated the standard deviation of this new quantity? Should I be using the pooled variance to calculate it? Or is there another approach that is better suited?
Here is an example of the data after spatially averaging. The light regions represent 95% confidence intervals. What I would like to do, is average the last 10 seconds of data (50--60 s) and calculate the corresponding standard deviation so that I can get confidence estimates for the mean.