11 if you multiply 11 by both the number and and the variable you’ll get 11x-55=66. Add 55 to each side which will give you 121 then divide that by 11
2
3
-7
24
-25
-3
second row
-12
-2
-9
-38
10
-28
Step-by-step explanation:
first u find the angles and then u use some low divide the length of triangle by sin of opposite angles
Answer:
Linear correlation exists
Step-by-step explanation:
Given the data :
X : | 2 4 5 6
Y : | 6 9 8 10
Using technology to fit the data and obtain the correlation Coefficient of the regression model,
The Correlation Coefficient, r is 0.886
To test if there exists a linear correlation :
Test statistic :
T = r / √(1 - r²) / (n - 2)
n = number of observations
T = 0.886 / √(1 - 0.886²) / (4 - 2)
T = 0.866 / 0.3535845
T = 2.449
Comparing Pvalue with α
If Pvalue < α ; Reject H0
Pvalue = 0.1143
α = 0.05
Pvalue > α ; We reject the null and conclude that linear correlation exists
Answer:
It is a perfect square. Explanation below.
Explanation:
Perfect squares are of the form
(
a
+
b
)
2
=
a
2
+
2
a
b
+
b
2
. In polynomials of x, the a-term is always x.(
(
x
+
c
)
2
=
x
2
+
2
c
x
+
c
2
)
x
2
+
8
x
+
16
is the given trinomial. Notice that the first term and the constant are both perfect squares:
x
2
is the square of x and 16 is the square of 4.
So we find that the first and last terms correspond to our expansion. Now we must check if the middle term,
8
x
is of the form
2
c
x
.
The middle term is twice the constant times x, so it is
2
×
4
×
x
=
8
x
.
Okay, we found out that the trinomial is of the form
(
x
+
c
)
2
, where
x
=
x
and
c
=
4
.
Let us rewrite it as
x
2
+
8
x
+
16
=
(
x
+
4
)
2
. Now we can say it is a perfect square, as it is the square of
(
x
+
4
)
.
