Null Hypothesis: A Fundamental Concept in Statistical Testing
by Yuvi K - December 30, 2023
What is the null hypothesis?
The null hypothesis is the assumed hypothesis in hypothesis testing during a statistical analysis. It is a statement that states that there is no significant difference between the sample and the intended population. To put it more simply, it is a statement that states that there is no meaningful relationship between two variables.
Why is the null hypothesis used?
The null hypothesis is a powerful tool that helps us assess if the observed results in a study are because of random chance or if they are statistically significant. By using the null hypothesis, researchers can determine if the results of their experiment really do prove what they hypothesize or if there is doubt in their results. In other words, researchers can use the null hypothesis to prove or disprove a relationship or outcome between the variables of interest.
How to conduct a hypothesis test using the null hypothesis?
When conducting a hypothesis test, the researcher first starts by creating two hypotheses: the null hypothesis (Ho) and the alternate hypothesis (Ha). The null hypothesis is the accepted hypothesis, and it states that there is no difference between the observed sample and the intended population. On the other hand, the alternate hypothesis states that there is a difference between the observed sample and the intended population.
Once the hypotheses are determined, the researcher then must calculate the probability that the sample observed will be statistically significant. This can be done through a variety of methods such as finding the probability of the alpha or commonly known as a p-value. A p-value is the probability that the sample data is the same or different when compared to the population. If the p-value is equal to or less than the predetermined alpha level (usually 0.05 or 0.01) then the null hypothesis is rejected and the alternate hypothesis is accepted.
Difference between Null Hypothesis and Alternate Hypothesis
| Null Hypothesis | alternative hypothesis |
|---|---|
| The null hypothesis is that there will be no difference between obviously unexpected elements or outcomes. | Alternative hypotheses are typified by commutativeness against the null hypothesis that there may be a difference between unexpected elements or outcomes. |
| Used in hypothesis testing. | Used to generate hypotheses in hypothesis testing. |
| This is the default option. | This is an optional option. |
| If it is continuous then it will be accepted as present on the basis of 8. | If this instruction is complete then it will become widespread. |
Conclusion
The null hypothesis is an important tool that helps researchers in hypothesis testing. It is essentially a statement that states that there is no difference between the sample observed in an experiment and the population. By calculating the probability of the sample being statistically significant, researchers can use the null hypothesis to validate or invalidate their results. The null hypothesis and the alternate hypothesis are two important hypothesis that are used to determine the validity of the results.
