Answer:
A Type I significance error occurs when a researcher claims to have found significant support for a hypothesis when there is not enough support to make this claim. A Type II significance error occurs when a researcher claims to have found no significant support for a hypothesis when there is actually enough to claim significance.
Explanation:
A significant error is seen in the hypothesis testing during the experimentation and research. Type I significance error occurs as a false positive, and type II significance error as a false negative.
The errors of the hypothesis testing are of two types namely type I significance error and a type II significance error. The type I significance error occurs if the null hypothesis is rejected by a researcher that was initially true and is denoted by false-positive.
The type II significance error occurs when a researcher is unable to falsify the null hypothesis that initially was not correct for the population, and is given as, false-negative.
Therefore, the type I and II significance error is contrasted based on the false-positive and false-negative.
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