<u>Explanation:</u>
a) First, note that the Type I error refers to a situation where the null hypothesis is rejected when it is actually true. Hence, her null hypothesis would be H0: mean daily demand of her clothes in this region should be greater than or equal to 100.
The implication of Type I error in this case is that Mary <u>rejects</u> that the mean daily demand of her clothes in this region is greater than or equal to 100 when it is actually true.
b) While, the Type II error, in this case, is a situation where Mary accepts the null hypothesis when it is actually false. That is, Mary <u>accepts</u> that the mean daily demand of her clothes in this region is greater than or equal to 100 when it is actually false.
c) The Type I error would be important to Mary because it shows that she'll be having a greater demand (which = more sales) for her products despite erroneously thinking otherwise.
I think it maybe greater than becuase i looked at the y intercept and it was a two ok so then i looked for a slope of 3x but in the picture the slope is only 2x.
3/4 + 1/8
you gotta find a common denominator
so you end up with
(24+4)/32
=28/32
7/8 is now complete
Answer:
113.1
Step-by-step explanation:
