Biometry — Introduction to Comparative Statistical Tests + 6 more topics

The core idea revolves around hypothesis testing:
* Null Hypothesis (H₀): There is no significant difference between the groups you're comparing. Any observed difference is due to random chance.
* Alternative Hypothesis (H₁): There is a significant difference between the groups. The observed difference is unlikely to be due to chance.

You collect data, run a statistical test, and get a p-value. The p-value tells you the probability of observing your data (or more extreme data) if the null hypothesis were true.

ANOVA, or Analysis of Variance, is a statistical test used to determine if there are significant differences between the means of three or more independent groups. It's an extension of the independent samples t-test, which only compares two groups.

The fundamental principle of ANOVA is to partition the total variability in your data into different components: