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:
X=53. X=38
Step-by-step explanation:
46+81+x=180
X=180-127
X=53 degrees
31+112+x=180
X=180-143
X=37 degrees
Answer:
Determine whether the statement is true or false.
13 € {1, 2, 3, ..., 10}
True
Let y be the total cost and x be the miles taken:
y = 0.30x + 35
35 is a fixed cost. No matter how many miles you drive the car you will still need to pay $35
.30 is a cost that depends on the miles taken (x).
Hope this helped!
~Just a girl in love with Shawn Mendes
