<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:
trapezium
Step-by-step explanation:
Well it's only B and D because like terms are where the variables are the same. This only happens at B and D because B has only jk's, and D only has x's
Answer:
Step-by-step explanation:
