Type I error happens when a difference is being observed when in truth, there is none or there is no statistically significant difference. This error is also known as false positive.
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type1 error is more dangerous
In statistics: type 1 error is when you reject the null hypothesis but it is actually true. Type 2 is when you fail to reject the null hypothesis but it is actually false. Statistical DecisionTrue State of the Null HypothesisH0 TrueH0 FalseReject H0Type I errorCorrectDo not Reject H0CorrectType II error
diabetes are two type 1insulin dependent diabetes 2 non insulin dependent diabetes
A combination of factors increase the risk of a Type 1 error. Giving the wrong amount or wrong diagnosis for a wrong drug would certainly increase an error.
It depends on whether it is the Type I Error or the Type II Error that is increased.