I think the correct answer from the choices listed above is the second option. The conclusion saying playing violin causes students to get better grades is a reasonable conclusion. This is because the correlation coefficient is above 0.5, so that implies causation. Hope this answers the question.
Answer:
(13 x 8) x 11 = 13 x (8 x 11)
Step-by-step explanation:
Using the Associative Property
2(3m-6+3m)=2m+2-4m
6m-12+6m=2m+2-4m
12m-12=-2m+2
14m-12=2
14m=14
m=1
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:
for second question
first length is 9cm
Area=l*b
= 9cm *9cm
=81<em><u>cm</u></em>
then, For semicircle
radius is 9 cm
area= 1/2*9cm
now , area of two semi circle = 2*1/2*9
= 9 cm
now area of shaded = 81-9
=72
