Why do Hypothesis testing?
The hypothesis test is made by a controlled experiment or a study made from the observation. Hypothesis is used to make decisions utilizing the data. Hypothesis test is a statistical test which also determines the significance of the result obtained from the testing. A statistically significant hypothesis or result of the test is considered not to have occurred by chance. This is determined based on the probability threshold called significance levelÃ¢â‚¬Â.
Hypothesis testing of a statistical analysis tells the extent of certainty of the quantified result of the statistical analysis. Hypothesis test is a statistical tool that can be applied in our real life activities. When any experiment is conducted with a sample population and if the result of the experiment has to be applied to a large population it is necessary to determine the significance of it. The statistical tests are applied in this case to decide how far the result is correct.
The components of a statistical test are null hypothesis, alternate hypothesis, test statistic, rejection region and conclusion. The hypothesis in the statistical analysis is made keeping in view of the proof created from contradicting the expected result of the experiment. For example, an experiment is conducted to determine the mean of a sample population. The testing is done to check whether there is rise or fall in the mean. To do this, a null hypothesis is made which will help to get the proof by generating a contradictory situation to the test result. In the above example, the null hypothesis states that there is no rise or fall in the mean value.
Statistical analysis will either accept or reject the null hypothesis. Alternate hypothesis assumes that there is either rise or fall of the mean. Hence, hypothesis testing forms an important part of the conclusion made for a statistical analysis. The aim of hypothesis testing is to indicate to us whether the proof for rejecting null hypothesis is reliable or not.