Easily Performing Statistical Tests Using Linear Models

Linear models are a statistical tool used to model the relationship between a dependent variable and one or more independent variables. They are based on the assumption that the relationship between the variables is linear, meaning that the change in the dependent variable is proportional to the change in the independent variables.

Linear models are widely used in many fields, including bioinformatics. In bioinformatics, linear models can be used to analyze large datasets, such as gene expression data. For example, linear models can be used to identify differentially expressed genes between different experimental conditions or to predict the expression of genes based on other variables, such as clinical data.

Linear models are closely related to statistical tests, such as t-tests and analysis of variance (ANOVA). In fact, t-tests and ANOVA can be seen as special cases of linear models. For example, a two-sample t-test is...