Hypothesis Testing: The Significance Of Null Hypothesis And Alternative Hypothesis In Comparing Populations Or Variables

No evidence against the null hypothesis: stick with it

What’s the interpretation of a p-value greater than 10%

When conducting a hypothesis test, the null hypothesis refers to a statement or assumption that there is no significant difference between two populations or variables. In contrast, the alternative hypothesis suggests that there is a significant difference between the populations or variables being compared.

The aim of a hypothesis test is to either reject or fail to reject the null hypothesis based on the available evidence. If the results of the test do not provide sufficient evidence to reject the null hypothesis, it is often recommended that the null hypothesis be retained. This means that no significant difference was found between the populations or variables being compared, and that any observed differences were likely due to chance.

Retaining the null hypothesis can be beneficial, as it can help to avoid making false conclusions or assumptions about the populations being studied. Therefore, it is important to ensure that the evidence is strong enough to reject the null hypothesis before accepting an alternative hypothesis.

In conclusion, if there is no significant evidence against the null hypothesis, it is wise to stick with it and avoid making false conclusions about the two populations or variables being compared.

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