Null hypothesis – Definition, Symbol and Example

What Is The Null Hypothesis?

• The null hypothesis is a statement that is presumed to be true until proven otherwise. It is used in statistics to test a hypothesis. The null hypothesis is always the opposite of the alternative hypothesis.
• The null hypothesis is a statement that is presumed to be true until it is shown to be false. The null hypothesis is always the opposite of the alternative hypothesis. In most cases, the null hypothesis is that there is no difference between the two groups being studied.

Why is Null Hypothesis Important?

• Null hypothesis is important because it is the basis for statistical testing. It is the hypothesis that is tested against the alternative hypothesis to see if the data supports the alternative hypothesis.
• Null hypothesis is important because it is the basis of statistical inference. It is the hypothesis that is tested for statistical significance. If the null hypothesis is rejected, then it is concluded that the alternative hypothesis is true.

Null Hypothesis Symbol

• Null hypothesis is a statement that the researcher tries to disprove. It states that there is no difference between the groups or that the population is not evenly split. The null hypothesis is symbolized with the letter H0.
• Null hypothesis symbol is a mathematical symbol used in statistics to denote the hypothesis that there is no difference between the means of two groups. The symbol is usually written as H0. The null hypothesis is usually contrasted with the alternative hypothesis, which is the hypothesis that there is a difference between the means of the two groups.

Example

The null hypothesis is a statement that is tested against an alternative hypothesis to determine the statistical significance of a result. The null hypothesis is that there is no difference between the groups being studied. The alternative hypothesis is that there is a difference between the groups being studied. The null hypothesis is usually the hypothesis that is tested when the researcher is not sure what the difference between the groups is.