Define these key terms

1. Null hypothesis: the hypothesis that there is no relationship between variables
2. P-value: the probability of obtaining our effect size or more extreme from the null hypothesis
3. Type I error: a false positive: rejecting the null hypothesis when there is no population effect
4. Type II error: a false negative, failing to reject the null hypothesis when there is a population effect

​Fill in the gaps

1. If you find a statistically significant result, using the most common value for alpha, your p-value must be less than 0.5
2. If you do not find a statistically significant result, you cannot reject the null hypothesis