The first is the null hypothesis (H0), which predicts that there will be no difference between the two variables being measured. For example, if we are measuring student performance in two different groups: one group is taught by a teacher who uses a theoretical approach to teaching, and the second group is taught by a teacher who has an interactive and engaging approach. The null hypothesis may predict that there is no difference in student performance between these two student groups.
The second hypothesis is the alternative hypothesis (H1), which further splits into two types: the two-tailed hypothesis (non-directional) and the one-tailed hypothesis (directional). The two-tailed hypothesis simply predicts that there will be a difference in student performance between these two groups but it does not predict the direction of this difference. The one-tailed hypothesis predicts specifically predicts the direction of the difference. For example, the one-tailed hypothesis may predict that students with the interactive teacher will perform better than students with the theoretical teacher.