Using error concepts for hypothesis tests, it is found that there is a Type I error.
A Type I error happens when a true null hypothesis is rejected.
A Type II error happens when a false null hypothesis is not-rejected.
In this problem, the null hypothesis is:
[tex]H_0: \mu = 24[/tex]
The alternative hypothesis is:
[tex]H_1: \mu > 24[/tex]
He concludes that the mean age is over 24 when it is not, that is, a true null hypothesis is rejected, hence there is a Type I error.
A similar problem is given at https://brainly.com/question/25225353
