* We recommend you have administrative rights and internet access as Windows users will need to install Rtools and grant R networking access to assigning tasks to individual cores (as parallel processing on Windows requires the use of ‘sockets’). Parallel processing can take time to set up, and unless you are doing tasks well suited to parallel processing (e.g. analysing multiple very large files), it is probably better (faster) to run your analyses as normal. Nevertheless, instructions for parallel processing below: The above example is an overly simplistic example. Using parallel processing on such a simple process is not efficient as there would be a neglible difference in processing time (/in actual fact, compiling data from different cores can lead to longer processing times when the actual analytical processing is not the bottleneck). Parallel processing should therefore be kept to CPU-intensive processing tasks (e.g. within machine learning). Though demonstrating this... View Article