average

I have a situation where I have one VERY large file that I'm using the linux "split" command to break into smaller parts. Later I use the linux "cat" command to bring the parts all back together again. In the interim, however, I'm curious... If I get an MD5 fingerprint on the large file before splitting it, then later get the MD5 fingerprints on all the independent file parts that result from the split command, is there a way to take the independent fingerprints and somehow deduce that the sum or average (or whatever you like to all it) of their parts is equal to the fingerprint of the single

I've recently created a C++ program to find the mean median and mode of an array of values. I realize this would be much better to do within a class. However, my function to generate the mean is not spitting out the right number, although I'm pretty certain the logic is fine. Also, I was able to modify a snipbit from something I found online to create a function that generates the mode, or at least the 1st most occurring values it can find, that I was able to implement. However, I am not 100% sure of how to wrap my head around what is actually happening within the function. A better

Code: ArrayList <Integer> marks = new ArrayList(); String output = "Class average:" + calculateAverage() + "\n" + "Maximum mark:" + calculateMaximum() + "\n" +"Minimum mark:" + calculateMinimum() + "\n" + "Range of marks:" + range; analyzeTextArea.setText(output); private double calculateAverage(double [] marks) { double sum = 0; for (int i=0; i< marks.length; i++) { sum += marks[i]; } return sum / marks.length; } Disregard the other things inside the string (minimum, maximum, and range) but for this line, String output = "Class average:" + calculateAverage() + "\n" + "Maximum mark:" +

Currently I'm trying to find a compact way to average a matrix . The obvious solution is to sum the matrix, then divide by the number of elements. I have, however, come across a method on the apple developer website that claims this can be done in a simpler way using valueForKeyPath. This is linked here: http://developer.apple.com/library/ios/#documentation/cocoa/conceptual/KeyValueCoding/Articles/CollectionOperators.html Here is the example I'm currently working on to try and get it to work: -(void)arrayAverager { NSMutableArray *myArray = [NSMutableArray arrayWithCapacity:25]; [myArray

horrible title, but let me explain: i've got this django model containing a timestamp (date) and the attribute to log - f.e. the number of users consuming some ressource - (value). class Viewers(models.Model): date = models.DateTimeField() value = models.IntegerField() for each 10seconds the table contains the number of users. something like this: | date | value | |------|-------| | t1 | 15 | | t2 | 18 | | t3 | 27 | | t4 | 25 | | .. | .. | | t30 | 38 | | t31 | 36 | | .. | .. | now i want to generate different statistics from this data, each with another resolution. f.e. for a chart of the last

Given a dataset of months, how do I calculate the "average" month, taking into account that months are circular? months = c(1,1,1,2,3,5,7,9,11,12,12,12) mean(months) ## [1] 6.333333 In this dummy example, the mean should be in January or December. I see that there are packages for circular statistics, but I'm not sure whether they suit my needs here. I think months <- c(1,1,1,2,3,5,7,9,11,12,12,12) library("CircStats") conv <- 2*pi/12 ## months -> radians Now convert from months to radians, compute the circular mean, and convert back to months. I'm subtracting 1 here assuming that January is