The level of significance is type I error
The level of significance is the measurement of the statistical significance. It defines whether the null hypothesis is assumed to be accepted or rejected.
In statistical hypothesis testing, a type I error is the mistaken rejection of an actually true null hypothesis, while a type II error is the failure to reject a null hypothesis that is actually false.
Beta error is the statistical error (said to be 'of the second kind,' or type II) that is made in testing when it is concluded that something is negative when it really is positive.
Here, Level of significance is the type I error because a type I error is a kind of fault that occurs during the hypothesis testing process when a null hypothesis is rejected, even though it is accurate
Hence, the level of significance is type I error
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