In designs where there are multiple factors, all with a discrete group of level settings, the full enumeration of all combinations of factor levels is referred to as a **full factorial design**. As the number of factors increases, potentially along with the settings for the factors, the total number of experimental units increases rapidly. Read the rest of this entry »

# Design of Experiments – Full Factorial Designs

December 1st, 2009# Design of Experiments – Power Calculations

November 18th, 2009Prior to conducting an experiment researchers will often undertake power calculations to determine the sample size required in their work to detect a meaningful scientific effect with sufficient power. In **R** there are functions to calculate either a minimum sample size for a specific power for a test or the power of a test for a fixed sample size. Read the rest of this entry »