![]() The likelihood of a Type I mistake is often calculated beforehand and is interpreted as the importance of testing the hypothesis.Therefore, type 1 error may come from chance or the level of significance chosen prior to the test, without taking into consideration the duration of the test or the size of the sample.Prior to testing a hypothesis, a probability is set as a level of significance, which means that the hypothesis is tested while acknowledging the possibility that the null hypothesis will be denied if it is correct.In actuality, though, it was decided by chance. In such circumstances, the outcome looks to have been driven by other factors besides chance.When a factor other than the variable influences the other variable and the outcome is such that the null hypothesis is supported, this is a type 1 mistake.This mistake might lead to the researcher concluding that the hypothesis holds true even when it does not.A type 1 mistake takes place when the null hypothesis is upheld even when there is no correlation between the variables. ![]()
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