A **hypothesis **is an assumption about one or more population parameters that is tested using statistical methods to determine whether there is enough evidence to reject or accept the hypothesis.

## Types of Hypothesis:

In statistical hypothesis testing, there are two main types of hypotheses:

## Null Hypothesis (H_{0}):

**Null Hypothesis** is the default assumption, often labeled **H-zero (H _{0})** that represents the idea that there is no effect, no difference, or no relationship in the population.

- It is also called as
**hypothesis of no difference**. - It represents the default assumption or the status quo (
**यथास्थिति**).

**Conditions of Null Hypothesis:**

**1.)** If we are interested to** test the significance** of the difference between a sample statistic and population parameter or between two sample statistics, **then **we set up the null hypothesis that there is no difference between the sample statistic and population parameter.

## Alternative Hypothesis (H_{1}):

**Alternative Hypothesis** is the research hypothesis, often denoted by H-a or H-one (H_{1}) that represents the opposite of the null hypothesis and states that there is an effect, difference, or relationship in the population.

- It is also called as
**hypothesis of difference**. - It could be directional (
**one-tailed**) or non-directional (**two-tailed**).