Respuesta :
Answer:
This explanation is not correct
Explanation:
Significance level is the probability that the null hypothesis rejected is in fact true. If we say there is a significance level of 0.10 or 10%(α=0.10 level) then there is a 10% chance of incorrectly rejecting the null hypothesis when there is actually no difference.
If we wish to reach a conclusion on rejection or acceptance of the null hypothesis, we could use the p value(the probability that observed results or more extremee results are true given null hypothesis)which we compare with the significance level to conclude. If the significance level is 0.10 and p value is 0.07(since p value is less than significance level) , we reject the null hypothesis and vice versa.
The significant level, α = 0.05 level specifies a probability of the correctness of the null hypothesis.
- The student is correct in the statement "This means that the probability that the null hypothesis is true is less than 0.05"
Reasons:
The significant level specifies the the likelihood of rejecting a true null
hypothesis, such that a 5% significance level indicates that the risk of
drawing a conclusion that there is a difference in a sample, when the
samples are similar is 5%, and therefore, the probability that null
hypothesis is true is 5% or 0.05.
The level of significance is a specification that indicates the amount of
evidence required within a sample to allow the rejection of the null
hypothesis, and reach a conclusion that the observed effect is statistical
significant at the α = 0.05 level.
Therefore;
The statement by the student that "This means that the probability that the null hypothesis is true is less than 0.05" is correct.
Learn more about hypothesis testing here:
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