MEAN: Compute means with standard errors. Mean reads data concerning the values of zero or more quantities from standard input, and writes the means of these quantities, with associated standard errors, to standard output. The values may come in batches, and may have associated weights, which are taken into account when computing the means and standard errors. For weighted data, the log of the mean weight and other quantities of interest are also computed. These are the only outputs if nothing but weights are present. Usage: mean [ -W | -w ] [ -b ] [ batch-size ] <data The data read from standard input must be in the form of a text file of numbers, with the same number of numbers on each line. If the -W or -w option is given, the first of these numbers is a weight (for -W) or the log of a weight (for -w). The remaining numbers on each line are values of the quantities whose means are to be computed. The lines are grouped into batches of size batch-size (default 1), with different batches assumed to be independent, but with possible dependence within a batch. The number of lines should be a multiple of the batch size, excepting blank lines (which are ignored); if not, the partial block at the end is discarded with a warning. If the -b (for "bare") option is present, the output consists of the (possibly) weighted means of each quantity, with standard errors, written with the mean and standard error for each quantity on a separate line, in high-precision exponential format, with no headers. As a special case, if -b and either -W or -w is given when there are no values (only weights), the log of the mean weight and its standard error are written to standard output, without headers. This "bare" output format is suitable for reading into some other program. If the -b option is not present, the means and standard errors are output in a more easily read (but perhaps less precise) form, with headers. Other information is also displayed, including the number of batches, the lines per batch, and, if -W or -w was specified, the log of the mean of the weights with its associated standard error and the adjusted sample size accounting for the variability of the weights. Standard errors are computed by first computing means and weights for each batch. The mean for a batch is simply the weighted mean of of values within that batch, and the weight for a batch is just the sum of the weights for lines within that batch. The weighted mean of the batch means is then computed, along with standard errors that assume these batch means are independent. The standard error for the mean of a quantity v with weighted mean m is given by sqrt ( sum_i w_i^2 (v_i - m)^2 ) / sum_i w_i^2 where w_i is the weight of the i'th batch, and v_i is the mean value of v for the i'th batch. The standard error for the log of the mean of the weights is computed by finding the standard error of the mean of the weights in the usual way, and then dividing by the mean of the weights. Note that this standard error cannot be trusted unless is it much less than one. The adjusted sample size is a general indication of accuracy that is not specific to any particular quantity. It is equal to (sum_i w_i)^2 / sum_i w_i^2 All the standard errors are probably not very reliable if the adjusted sample size is less than ten. Copyright (c) 1995-2004 by Radford M. Neal