Answer:
yes
Step-by-step explanation:
6.80
6.75 8 is greater then 7 therefore 6.80 is greater
16 (i believe so)
4.05 divided by 0.25 is 16.2- but you must round to the nearest tenth- you cant make a 0.2 hamburger
Solving for x would give me 14 and negative 10 which would lead to the problem looking like so 14(-10-4)=140
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
Step-by-step explanation:
<u>Given </u><u>:</u><u>-</u>
And we need to solve the equation using Substituting method . So on taking the first equation ,
<u>Put </u><u>this</u><u> </u><u>value</u><u> </u><u>in </u><u>(</u><u>ii)</u><u> </u><u>:</u><u>-</u><u> </u>
<u>Put </u><u>this</u><u> </u><u>Value</u><u> </u><u>in </u><u>(</u><u>I)</u><u> </u><u>:</u><u>-</u><u> </u>
<u>Hence</u><u> the</u><u> </u><u>Value</u><u> </u><u>of </u><u>x </u><u>is </u><u>2</u><u>1</u><u> </u><u>and </u><u>y </u><u>is </u><u>(</u><u>-</u><u>6</u><u>)</u><u> </u><u>.</u>