What is the null hypothesis? Why is the null hypothesis important? A null hypothesis occurs when samples are taken in inferential statistics but those samples are not representative due to random sampling errors. This can happen in three ways: 1. The observed difference was created by sampling errors, keeping in mind that there is no bias since the survey is performed randomly. 2. The null hypothesis also occurs when there is no true difference between the two groups. This means that the real difference is what a researcher would find if there were no sampling errors. 3. The true difference between the two groups is zero. The null hypothesis is important to determine whether there is a difference between the groups tested or not. If the null hypothesis were not present, the number of possibilities would make testing impossible. Even at the beginning of the research the null hypothesis can make the research more objectively grounded and play a key role in the statistical analysis as the results become available. Ultimately, therefore, with the degree of the null hypothesis and its probability (p) it is possible to determine it rather than reject it in place of the alternative hypothesis (Patten,