A type I error takes place if a given null hypothesis is rejected but is said to be true in the population such as the forecast shows it is snowing outside but actually it is isn't.
<h3>What is type 11 error?</h3>
A type II error is known to be a statistical term that tells the error that takes place when one fails not to accept a null hypothesis that is said to be really false. A type II error create a false negative.
- It known is known also as an error of omission. Example is the forecast shows that It is not snowing but it is actually snowing.
Note that:
- Type I error is false positive.
- Type II error is false negative.
The power of the test shows that:
- The Power is the likelihood of rejecting the null hypothesis even if it is false.
- Power is the likelihood of making the right decision that is to reject the null hypothesis even if the null hypothesis is false.
- Power is the likelihood of not making a Type II error and others.
See full question below
Suppose you have the following null and alternative hypothesis:
H o: it is snowing.
H a: It is not snowing
(A) in the context of this problem, describe a Type-1 error
(B) Describe Type II error
(C)Describe power of the test
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