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: 540sqrt2
Step-by-step explanation:
In this situation you will need to do 8 divided by 25 which will give the answer 0.32.
Answer:
649 trains
Step-by-step explanation:
If there are 30 seats per carriage, and there is 18 carriages per train.
You multiple 30 and 18 to get how many seats there are in a train.
30*18 is 540 seats.
To figure out how many trains would be needed to seat 350,000 passenger, you have to divide 350,000 with 540 to get how many trains would be needed.
350,000/540 is 648.1
Since the answer is 648.1 and you can't chop a train into 10 pieces, you would need 649 trains to seat 350, 000 passengers.
