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 using say two different operators, who would be expected to display different degrees of competence with the equipment. Or we might not be able to run all of the experimental combinations in one session so we would want to take into account systematic differences that are due to experiments in the various sessions. Read the rest of this entry »

# Design of Experiments – Block Designs

February 20th, 2010# Two-way Analysis of Variance (ANOVA)

February 15th, 2010The analysis of variance (**ANOVA**) model can be extended from making a comparison between multiple groups to take into account additional factors in an experiment. The simplest extension is from one-way to two-way **ANOVA** where a second factor is included in the model as well as a potential interaction between the two factors. Read the rest of this entry »

# One-way ANOVA (cont.)

February 12th, 2010In a previous post we considered using **R** to fit one-way ANOVA models to data. In this post we consider a few additional ways that we can look at the analysis. Read the rest of this entry »

# One-way Analysis of Variance (ANOVA)

February 3rd, 2010Analysis of Variance (**ANOVA**) is a commonly used statistical technique for investigating data by comparing the means of subsets of the data. The base case is the one-way **ANOVA** which is an extension of two-sample t test for independent groups covering situations where there are more than two groups being compared. Read the rest of this entry »