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A statistical test is always a test on your Null Hypothesis and tests the probability that your Null Hypothesis is valid. The 5 most commonly used statistical tests are:

  1. Standard t-test
  2. Paired t-test
  3. One-way Analysis of Variance (ANOVA)
  4. Two-way ANOVA
  5. Linear Regression

Each of these five tests is a statistical comparison of two (or more) means from each separate group in the experiment.

Standard t-test

The standard t-test is used to compare the means from exactly two groups, such as the control versus the experimental group.


There are two types of categorical variables: a nominal categorical variable and an ordinal categorical variable. A nominal variable is a categorical variable without an implied order. This means it is impossible to say that 'one is worth more than the other'. Think for example of the categorical variable animals_vector, with the categories "Elephant", "Giraffe", "Donkey" and "Horse". Here, it is impossible to say one stands above or below the other. In contrast, ordinal variables do have a natural ordering. Consider for example the categorical variable temperature_vector with the categories: "Low", "Medium" and "High". Here it is obvious that "Medium" stands above "Low", and "High" stands above "Medium".

  • Multivariate analysis (MVA) refers to methods for the analysis of data containing more than one variable
    • One of the problems with MVA is data visualisation since it becomes difficult to visualise three or more variables

Reading list