Question

In hypothesis testing, we state two different hypotheses? What are they? As researcher, which do we believe to be true? Which do we assume to be true at first and put to the test?

Answer 1

The null and alternative hypotheses are two mutually exclusive statements about a population. A hypothesis test uses sample data to determine whether to reject the null hypothesis.

Null hypothesis H​​​​​​0

The null hypothesis states that a population parameter (such as the mean, the standard deviation, and so on) is equal to a hypothesized value.The null hypothesis is often an initial claim that is based specialized knowledge. The null hypothesis is hypothesis of no difference.

Alternative hypothesis H​​​​​​1

The alternative hypothesis states that a population parameter is smaller, greater, or different than the hypothesized value in the null hypothesis. The alternative hypothesis is what you might believe to be true or hope to prove true.

According to R.A Fisher (Father of Statistics), Null hypothesis is tested for possible rejection. So,

Researcher believe Alternative hypothesis to be true. So what researcher believe is put on the alternative hypothesis and the one which is believed not to be true is put on Null hypothesis.