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.
<h2>Answer :</h2>
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So in a proportion 23.4 over 5.49 equals 1 over o and multiply 5.49•1=23.4o
5.49=23.4o divide by 23.4 on both sides and that equals 4.26 per oz
Answer:
Equally likely
Step-by-step explanation:
Equally likely means that it’s a 50% percent chance on both sides meaning that equally likely Is the answer.
Therefore, the total costs for year 1 will be $2,240, for year 2 they will be $2,040, and for year 3 they will be $2,120.
<h3><u /></h3><h3><u>Costs</u></h3>
Given that one of your company's salesmen estimates he will drive 20,000 miles this year and each of the next two years, and as the service manager for the company's fleet of six-cylinder compact automobiles, you are asked to determine the total costs for each of the three years, to determine said cost, the following calculation must be made:
- Year 1:
- 20000 x 0.112 = X
- 2,240 = X
- Year 2:
- 20000 x 0.102 = X
- 2,040 = X
- Year 3:
- 20000 x 0.106 = X
- 2,120 = X
Therefore, the total costs for year 1 will be $2,240, for year 2 they will be $2,040, and for year 3 they will be $2,120.
Learn more about costs in brainly.com/question/4557688
