Generation of the hypothesis is the beginning of a scientific process. It refers to a supposition, based on reasoning and evidence. The researcher examines it through observations and experiments, which then provides facts and forecast possible outcomes. The hypothesis can be inductive or deductive, simple or complex, null or alternative. Null hypothesis implies a statement that expects no difference or effect. On the contrary, an alternative hypothesis is one that expects some difference or effect. This article excerpt shed light on the fundamental differences between null and alternative hypothesis.
Content: Null Hypothesis Vs Alternative Hypothesis
|Basis for Comparison||Null Hypothesis||Alternative Hypothesis|
|Meaning||A null hypothesis is a statement, in which there is no relationship between two variables.||An alternative hypothesis is statement in which there is some statistical significance between two measured phenomenon.|
|Represents||No observed effect||Some observed effect|
|What is it?||It is what the researcher tries to disprove.||It is what the researcher tries to prove.|
|Acceptance||No changes in opinions or actions||Changes in opinions or actions|
|Testing||Indirect and implicit||Direct and explicit|
|Observations||Result of chance||Result of real effect|
|Mathematical formulation||Equal sign||Unequal sign|
Definition of Null Hypothesis
A null hypothesis is a statistical hypothesis in which there is no significant difference exist between the set of variables. It is the original or default statement, with no effect, often represented by H0 (H-zero). It is always the hypothesis that is tested. It denotes the certain value of population parameter such as µ, s, p. A null hypothesis can be rejected, but it cannot be accepted just on the basis of a single test.
Definition of Alternative Hypothesis
A statistical hypothesis used in hypothesis testing, which states that there is a significant difference between the set of variables. It is often referred to as the hypothesis other than the null hypothesis, often denoted by H1 (H-one). It is what the researcher seeks to prove in an indirect way, by using the test. It refers to a certain value of sample statistic, e.g., x¯, s, p
Key Differences Between Null and Alternative Hypothesis
The important points of differences between null and alternative hypothesis are explained as under:
- A null hypothesis is a statement, in which there is no relationship between two variables. An alternative hypothesis is a statement; that is simply the inverse of the null hypothesis, i.e. there is some statistical significance between two measured phenomenon.
- A null hypothesis is what, the researcher tries to disprove whereas an alternative hypothesis is what the researcher wants to prove.
- A null hypothesis represents, no observed effect whereas an alternative hypothesis reflects, some observed effect.
- If the null hypothesis is accepted, no changes will be made in the opinions or actions. Conversely, if the alternative hypothesis is accepted, it will result in the changes in the opinions or actions.
- As null hypothesis refers to population parameter, the testing is indirect and implicit. On the other hand, the alternative hypothesis indicates sample statistic, wherein, the testing is direct and explicit.
- A null hypothesis is labelled as H0 (H-zero) while an alternative hypothesis is represented by H1 (H-one).
- The mathematical formulation of a null hypothesis is an equal sign but for an alternative hypothesis is not equal to sign.
- In null hypothesis, the observations are the outcome of chance whereas, in the case of the alternative hypothesis, the observations are an outcome of real effect.
There are two outcomes of a statistical test, i.e. first, a null hypothesis is rejected and alternative hypothesis is accepted, second, null hypothesis is accepted, on the basis of the evidence. In simple terms, a null hypothesis is just opposite of alternative hypothesis.