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.
You can use Guess and Check and divide the 50 pounds into 2 parts. Multiply the price for both and do square root for the prices. Then at the 2 square roots and see if they add up to $6.40. If not, then divide the 50 pounds into something else, like 30 and 20 or something like that.
I think it is A, a glass of water can contain about 200-250 ml.
2.5 rounded to the nearest tenth is: 3
3.5 rounded to the nearest tenth is: 4
2 rounded to the nearest tenth is: 2
Answer:
sheesh
Step-by-step explanation:
