<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.
Answer:
the inverse is(sorry if this is not what your looking for
Step-by-step explanation:
f^-1(x)=2x-4
I want to say A because 3 and 5 have 15 and 6:15 is sounds like a ratio and D is just 4/10
What are you stuck on ??????
When we have a High Outlier in the data-set the line will extend from the Q3 to "Q3+1.5*IQR", which is considered the Maximum value, therefore the answer is True. The outlier will be a point outside this range.
