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 (H0):
Null Hypothesis is the default assumption, often labeled H-zero (H0) 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 (H1):
Alternative Hypothesis is the research hypothesis, often denoted by H-a or H-one (H1) 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).
