![]() ![]() It can never “prove” the null hypothesis, because the lack of a statistically significant effect doesn’t mean that absolutely no effect exists. It’s important to note that hypothesis testing can only show you whether or not to reject the null hypothesis in favor of the alternative hypothesis. Otherwise, you can easily manipulate your results to match your research predictions. This makes the study less rigorous and increases the probability of finding a statistically significant result.Īs best practice, you should set a significance level before you begin your study. The significance level may also be set higher for significance testing in non-academic marketing or business contexts. That means an effect has to be larger to be considered statistically significant. The significance level can be lowered for a more conservative test. That means your results must have a 5% or lower chance of occurring under the null hypothesis to be considered statistically significant. Usually, the significance level is set to 0.05 or 5%.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |