One-Way ANOVA Analysis of variance is a tool used for a variety of purposes. Applications range from a common one-way ANOVA, to experimental blocking, to more complex nested designs. This first ANOVA example provides the necessary tools to analyze data using this technique. This example will show a basic one-way ... [Read more...]

The FrF2 package for R can be used to create regular and non-regular Fractional Factorial 2-level designs. It is reasonably straightforward to use. First step is to install the package then make it available for use in the current session: require(FrF2) A basic call to the main functino FrF2 ... [Read more...]

The Balanced Incomplete Block Design (BIBD) is a well studied experimental design that has various desirable features from a statistical perspective. The crossdes package in R provides a way to generate a block design for some given parameters and test wheter this design satisfies the BIBD conditions. For a BIBD ... [Read more...]

In many experiments where the investigator is comparing a set of treatments there is the possibility of one or more sources of variability in the experimental measurements that can be accounted for during the design stage of the experimentation. For example we might be investigating four different pieces of machinery ... [Read more...]

[Read more...]

[Read more...]

[Read more...]

When considering using a full factorial experimental design there may be constraints on the number of experiments that can be run during a particular session, or there may be other practical constraints that introduce systematic differences into an experiment that can be handled during the design and analysis of the ... [Read more...]

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 ... [Read more...]

When designing an experiment it is not always possible to generate a regular, balanced design such as a full or fractional factorial design plan. There are usually restrictions of the total number of experiments that can be undertaken or constraints on the factor settings both individually or in combination with ... [Read more...]

Prior 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 ... [Read more...]