Angles A and G.
Hope this helps.
Two different things u can do
Substitution:
X-9y=12
+9y +9y
X=9y+12
-3(9y+12)+9y=36
-27y-36+9y=36
+36 +36
-18y = 72
/-18 /-18
Y = -4
Or whatever this other I’ve is called
-3x-9y=36
-1(X-9y)=(12)-1
-3x-9y=36
-x+9y=-12
-4x=24
X= -6
Answer:
Point
Step-by-step explanation:
Just see it like this
we have a cube, so we have x-, y- and z- axis.
Now if we divide this cube by its z- value we will have a 2 dimensional figure with x- and y- axis.
If we keep doing this we will have a 1 dimensional figure with only a x - axis (a line) and if we divide that 1 more time we will make the figure collapse in 1 point.
I hope this helps you
Brandon x
Michael 3x
18 years ago
Brandon x-18
Michael 3x-18
9 (x-18)=3x-18
9x-9.18=3x-18
9x-3x=9.18-18
6x=8.18
x=8.3
x= 24
Answer:
0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x
Step-by-step explanation:
Given the data in the question;
sample size n = 28
slope of the least squares regression line of y on x or sample estimate = 0.0623
standard error = 0.0224
95% confidence interval
level of significance ∝ = 1 - 95% = 1 - 0.95 = 0.05
degree of freedom df = n - 2 = 28 - 2 = 26
∴ the equation will be;
⇒ sample estimate ± ( t-test) ( standard error )
⇒ sample estimate ± (
) ( standard error )
⇒ sample estimate ± (
) ( standard error )
⇒ sample estimate ± (
) ( standard error )
{ from t table; (
) = 2.055529 = 2.056
so we substitute
⇒ 0.0623 ± ( 2.056 )( 0.0224 )
Therefore, 0.0623 ± ( 2.056 )( 0.0224 ) can be used to compute a 95% confidence interval for the slope of the population regression line of y on x