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: The height of tree = 15 ft. 6 inches
Step-by-step explanation:
Given: A person's height is 5-ft 3-in = [5 x (12 )+3 ] inches [ 1 ft= 12 inches]
= 63 inches
Their shadow has a length of 3-ft 6-in = [3 x 12+6] inches
= 42 inches
If a nearby tree has a shadow of length 10-ft 4-in = [10 x 12+4] inches
= 124 inches.
At the same time,
Hence, the height of tree = 15 ft. 6 inches
Answer:
if am correct your answer will be letter d
Step-by-step explanation:
Answer:2/16
Step-by-step explanation:
-2(x + 3) = 8
Multiply -2 with x and 3
-2x -6 = 8
Now add 6 to both sides
-2x -6 = 8
+6 +8
-2x = 16
Lastly divide -2 from both sides to find x
-2x = 16
—— —-
-2x -2x
X = -8
