Question

The null hypothesis is often referred to as the status quo as it represents how things have been or are typically expected to be. The alternate hypothesis is what we believe has changed.

Why should the alternate hypothesis be the exact opposite of the null hypothesis?

Answer 1

The null hypothesis is often referred to as the status quo as it represents how things have been or are typically expected to be. The alternate hypothesis is what we believe has changed or the claim we do.

In Inferential statistics, to check for the significance of the alternate hypothesis, we assume that the null hypothesis is true and based on given sample data, we try to find the probability of finding the observed, or more extreme, results when the null hypothesis is true (p-value). If the p-value is low, we infer that based on data the null hypothesis cannot be true and can be rejected. Once null hypothesis is rejected, there is significant evidence that the exact opposite of the null hypothesis is true. If the alternate hypothesis be the exact opposite of the null hypothesis, we are able to significantly prove that what we believe or claim is true. If the alternate hypothesis is not the exact opposite of the null hypothesis, we cannot infer anything even if we are able to reject the null hypothesis.