It’s written in slope intercept form .
Can you post this and provide a picture please so I can help you ?
Explanation:
Jill had a total score of 40 on 13 quizzes, so her average was
40/13 ≈ 3.08
_____
1 quiz @ 1 = total of 1
3 quizzes @ 2 = total of 6
4 quizzes @ 3 = total of 12
4 quizzes @ 4 = total of 16
1 quiz @ 5 = total of 5
total score = 1 + 6 + 12 + 16 + 5 = 40
total quizzes = 1 + 3 + 4 + 4 + 1 = 13
<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.
12:7
because you add 7 and 5 and then there is the 7 for the book weight
