The best answer from the options that proves that the residual plot shows that the line of best fit is appropriate for the data is: ( Statement 1 ) Yes, because the points have no clear pattern
X Given Predicted Residual value
1 3.5 4.06 -0.56
2 2.3 2.09 0.21
3 1.1 0.12 0.98
4 2.2 -1.85 4.05
5 -4.1 -3.82 -0.28
The residual value is calculated as follows using this formula: ( Given - predicted )
1) ( 3.5 - 4.06 ) = -0.56
2) ( 2.3 - 2.09 ) = 0.21
3) ( 1.1 - 0.12 ) = 0.98
4) (2.2 - (-1.85) = 4.05
5) ( -4.1 - (-3.82) = -0.28
Residual values are the difference between the given values and the predicted values in a given data set and the residual plot is used to represent these values .
attached below is the residual plot of the data set
hence we can conclude from the residual plot attached below that the line of best fit is appropriate for the data because the points have no clear pattern ( i.e. scattered )
learn more about residual plots : brainly.com/question/16821224
Answer:
a
Step-by-step explanation:
CB and GF are the same side and u can see that CB is two times larger than GF so GH is two times smaller then CD
You can do this by doing 4 x 384, and you also want to find 4 x 5384 is then all you have to do is multiply the product of that by 5,000. Or to make life easier, do 5 times the product, and then add 3 zeros to the answer.
Answer:
(x+1)^2
Step-by-step explanation:
(g ° f) (x) = g(f(x))
g ( f(x)) means that you are going to replace x in g(x) for f(x)
g(x) = x^2
f(x) = x+1
So you have to solve g(x) when x = x+1
g (x+1) = (x+1)^2