Answer :
The level of significance chosen for the hypothesis test is equivalent to the likelihood of making a type I error. Therefore, there is a 5% probability that a type I mistake could happen if the threshold of significance is 0.05.
The degree of statistical significance (also known as alpha) is the probability of making a type I error, which is rejecting the null hypothesis when it is actually true.
The likelihood of rejecting the null when it is TRUE is known as a Type I mistake. The error of false rejection is another name for a type I error. To put it another way, when a type I error happens, the statistician incorrectly rejects the null hypothesis even when it is true.
As a result, if the null hypothesis is correct, rising increases the likelihood that we will make a Type I error (rejecting a true null hypothesis).
A false alarm will come from a type I error. There will be a false positive as a result of the hypothesis testing. This suggests that the researcher decided that a hypothesis testing result was accurate when, in actuality, it was not.
How likely is it that you will commit a Type I error? Given that a Type I error only happens when the choice to reject the null hypothesis is taken, the likelihood of committing this kind of error is equal to the likelihood of doing so.
Therefore,
The level of significance chosen for the hypothesis test is equivalent to the likelihood of making a type I error. Therefore, there is a 5% probability that a type I mistake could happen if the threshold of significance is 0.05.
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