I think the correct answer would be B. If the residuals for brand A form an increasing curve, and the residuals for brand B form a U-shaped pattern, then neither of the data is likely to be linear. In order to be linear, the residuals of both data set should be, more or less, linear or approaching linearity in nature. Therefore, the linear regression that was done would not give good results since it is only applicable to linear data sets. Also, you can say that the relation of the data sets of the products are not linear. It would be best to do a curve fitting for both sets by using different functions like parabolic functions.
Answer:
2
Step-by-step explanation:
10a² : 5a² = 10 : 5 = 2
Answer:
Step-by-step explanation:
Given that g is a function from g : {1, 2, 3} ->{1, 2, 4, 8}
by the function
i.e. we have 
Range = {2,4,8} Since there is an extra element 1 in the co domain which is not in range , g is not on to
But g is one to one as 1,2,3 have different images.
