We explain a statistical method to compare more than two groups.

🎓️ When comparing the means of two independent groups we use the well-known t-test.

❓️But what to do if we have more than two groups?

Statistical Method:

📊 The generalization of the t-test for three or more groups is the ANOVA (Analysis of Variance).

📊 In its simplest version the ANOVA measures the influence of one categorical variable on the means of the groups, but we can also include more factors.

📊When considering two or more factors, it is important to take possible interactions between the factors into account. This can also be integrated into the model.

📊 When also including continuous covariates, we use an ANCOVA (Analysis of Covariance).

Keep in mind:

⚠️ Since the ANOVA is a generalization of the t-test, we have the same assumptions: independence of the groups, homogeneity of variance and normal distributed data.

🔜 In our next post you will learn which models you can use in the scenario of repeated measurements, since in this case the independence assumption is not fulfilled.

 📢 Stay tuned and continue building statistical confidence for market access.