This low probability then allows us to reject the null hypothesis in favour of the more biologically interesting alternative hypothesis.
t-statistic, F-value, etc.), and rejected the null hypothesis when the observed test statistic falls outside the test statistic distribution with some arbitrarily low probability (e.g. Up to now, when faced with a biological question, we have formulated a null hypothesis, generated a model to test the null hypothesis, summarized the model to get the value of the test-statistic (e.g. 01: Linear models and statistical modelling 19: Data wrangling in dplyr, ggplot, tidy data 10: Intro to course, programming, RStudio, and R Markdown
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