What is the relationship between the null hypothesis and the alternate hypothesis?

I have been studying statistics for a few years now, and one vital part of the science of statistics is the hypothesis test.

When conducting a hypothesis test, the researchers must first state the hypothesis by defining the null hypothesis and alternate hypothesis:-

• The null hypothesis (H0) states that there is no effect or relationship.
• The alternate hypothesis (Ha or H1) states there is a significant difference.

In hypothesis testing, researchers aim to disprove the null hypothesis by gathering evidence that supports the alternate hypothesis, effectively treating them as mutually exclusive options:-

• The null and alternate hypothesis are designed to be mutually exclusive, meaning they are the exact opposite of each other. If one is true, the other must be false.
• The null and alternate hypothesis offer different answers to a research question. For example, if the question is whether a new drug works, the null hypothesis would state that the drug has no significant effect, while the alternate hypothesis would state the drug has a significant effect.

In the hypothesis testing process, the researcher assumes the null hypothesis is true until there is enough evidence to suggest otherwise. The goal of the study is to reject the null hypothesis in favour of the alternate hypothesis.

If the results of the test are not statistically significant then the null hypothesis is not rejected, thereby providing support to the alternate hypothesis.

The example below is a one sample t-test that determines the weight loss of a sample group. The average weight loss of the group is 5.26 while the population mean is 5. Therefore, the null hypothesis is rejected because there is a significant difference between the sample mean and the population mean:-

Statistics is a fascinating subject and understanding the null hypothesis and alternate hypothesis are the first things that must be decided when conducting any research.