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.
No you have to move the decimal place over 2 times to the left
Answer:
No mabey c
Step-by-step explanation:
Answer:
The mean is the average of the numbers. It is easy to calculate: add up all the numbers, then divide by how many numbers there are.
Step-by-step explanation:
b=16 , First you multiply 30 by 2 to see what sum you need for the numerator. Then you subtract the 60 that you get by the 12 and get 48. So 3 multiplied by b should give you 48. So you just divide 48 by 3 and get 16.
