# Test Yourself

## True or False

#### Feedback

**False**

**The p-value is the probability of observing a difference as extreme as what was observed assuming the null hypothesis is true. So a p-value greater than 0.05 suggests that there's more than a 1 in 20 chance of seeing a difference between 2 groups as big as we observed if the null hypothesis is true. It is thus a measure of the strength of evidence against the null hypothesis. In this example we would therefore suggest that there is insufficient evidence to reject the null hypothesis. This does not mean that the null is true, it just means there's an absence of evidence against it. Besides, we can never logically prove a hypothesis, only falsify it.**