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:
-j, 0, j-k
Step-by-step explanation:
j is a positive number, so -j will be less than 0.
j is a number greater than k, so j - k will be greater than 0.
From least to greatest, the order is ...
-j, 0, j-k
Answer:
get x isolated
Step-by-step explanation:
Answer:
33%
Step-by-step explanation:
Since the probability of rain on Thursday is 67%, the probability of no rain on Thursday is 100% - 67% = 33%.