One of the most frequent used techniques in statistics is linear regression where we investigate the potential relationship between a variable of interest (often called the response variable but there are many other names in use) and a set of one of more variables (known as the independent variables or some other term). Unsurprisingly there are flexible facilities in **R** for fitting a range of linear models from the simple case of a single variable to more complex relationships. Read the rest of this entry »

# Simple Linear Regression

April 23rd, 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 »