Answer (x,y) (3, -2)
Explanation:
using the
substitution method
y
=
x
−
5
→
(
1
)
y
=
−
2
x
+
4
→
(
2
)
since both equations are expressed in terms of x we
can equate them
⇒
x
−
5
=
−
2
x
+
4
add 2x to both sides
2
x
+
x
−
5
=
−
2
x
+
2
x
+
4
⇒
3
x
−
5
=
4
add 5 from both sides
3
x
+
5
−
5
=
4
+
5
⇒
3
x
=
9
divide both sides by 3
3
x
3
=
9
3
⇒
x
=
3
substitute this value in
(
1
)
y
=
3
−
5
=
−
2
As a check
substitute these values into
(
2
)
right
=
−
6
+
4
=
−
2
=
left
⇒
point of intersection
=
(
3
,
−
2
)
L=16
W=21
Set up a systems of equations:
x=length
y=width
xy=336
x+5=y
Use substitution to solve:
x(x+5)=336
x^2+5x=336
Solve using factoring:
x^2+5x-336=0
(x-16)(x+21)=0
x=16 and x= -21
Since length can't be negative, l=16
To find width, plug length into the first equation:
(16)y=336
y=21
So...
L=16
<span>W=21</span>
Answer:
my estimation is 67
Step-by-step explanation:
K is equal to 3. to find this i used the slope formula y2-y1/x2-x1. 4-k/-1-2
-1-2=-3 so that means that 4-k has to equal 1. 4-3=1
k=1
Step-by-step explanation:
First, note that a flexible statistical learning method refers to using models that take into account agree difference in the observed data set, and are thus adjustable. While the inflexible method usually involves a model that has no regard to the kind of data set.
a) The sample size n is extremely large, and the number of predictors p is small. (BETTER)
In this case since the sample size is extremely large a flexible model is a best fit.
b) The number of predictors p is extremely large, and the number of observations n is small. (WORSE)
In such case overfiting the data is more likely because of of the small observations.
c) The relationship between the predictors and response is highly non-linear. (BETTER)
The flexible method would be a better fit.
d) The variance of the error terms, i.e. σ2=Var(ϵ), is extremely high. (WORSE)
In such case, using a flexible model is a best fit for the error terms because it can be adjusted.
