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Question - Type I and Type II errors Contains unread posts Statistically speaking, we are generally agnostic to which is a bigger problem, type I (false positive) errors or type II (false negative) errors. However, in certain circumstances it may be important to try and put more emphasis on avoiding one or the other. Can you think of an example of where you may want to try harder to avoid one type or another? Can you think of a policy; political, economic, social, or otherwise, that pushes people toward avoiding one type or another? What are the repercussions of such policies?
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This task provides a clear working example of Type I Error and Type II Error.Type I Error occurs when the researcher reject the null hypothesis but in real situation, the null hypothesis should not be rejected. Type II Error occurs when the researcher fails to reject the null hypothesis but in real situation, the null hypothesis should be rejected.
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