Hi, I have a question concerning the calculation of the confidence interval of the mean of a measured variable.
I am running several (m>30) simulation runs with same parameters but different random seeds. In each of these simulation runs, n samples (usually several thousand) of a measured variable are taken. In my simulations, the samples within each simulation run can not be assumed to be independent. However, according to the literature I read so far, the sample means of the different simulation runs are normally distributed (due to the central limit theorem). In the literature, it is assumed that the number of samples (n) is the same for each simulation run. With this assumption the confidence interval of the mean is calculated by: overall_sample_mean +/- z_value* ( standard_dev_of_the_sample means) However, in my experiments the number of samples (n) is not the same for each simulation run, but slightly different (e.g. 3105, 2934, 3050,...). My question: does this matter? Or can I still use the above formula? Thanks in advance! Jacek Gomoluch . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
