Final answer:
The Type I error would be to reject the null hypothesis when it is true, and the Type II error would be to fail to reject the null hypothesis when it is false.
Step-by-step explanation:
The owner of a football team claims that the mean attendance at games is over 59,100, and he is therefore justified in moving the team to a city with a larger stadium. The null hypothesis (H0) would be that the mean attendance is 59,100 or less. The alternative hypothesis (Ha) would be that the mean attendance is greater than 59,100.
The Type I error in this case would be to reject the null hypothesis (H0) when it is true, which means concluding that the mean attendance is over 59,100 when it is actually 59,100 or less. The Type II error would be to fail to reject the null hypothesis (H0) when it is false, which means not concluding that the mean attendance is over 59,100 when it is actually greater than 59,100.