A parallel line has the same slope as the original line. So in this case the slope of the line is also 3/4. Now how do we know if it intersects the point? We need to adjust the y intercept.
Currently, we know the equation of the line is y= 3/4 x + b, where b is the thing we are looking for. We also have a point, which supplies the x and y. Plug that in and solve for b
-2 = (3/4)*(12) + b
You'll get b= -11
So the equation of the parallel line intersecting the point given is y= 3/4x -11.
I am assuming that the slope is 3/4 based on the way you formatted the original equation, but it's the same steps if the slope is different.
Answer:
2.26 feet
Step-by-step explanation:
400/25=16
16/3.14=5.0955
5.0955^2=2.257
Answer:
A. (-1, -4)
Step-by-step explanation:
The vertex can be found by converting the equation from standard form to vertex form.
<h3>Vertex</h3>
Considering the x-terms, we have ...
y = (x^2 +2x) -3
where the coefficient of x is 2. Adding (and subtracting) the square of half that, we get ...
y = (x^2 +2x +(2/2)^2) -3 -(2/2)^2
y = (x +1)^2 -4
Compare this to the vertex form equation ...
y = a(x -h)^2 +k
which has vertex (h, k).
We see that h=-1 and k=-4. The vertex is (h, k) = (-1, -4).
On the attached graph, the vertex is the turning point, the minimum.
Answer:
The answer would have came out of 3.84615384615
Then round up the answer to 3.85. So the unit price is $3.85
The first answer is a letter c - normal
distribution. The normal distribution is the most significant
and most generally used distribution in statistics. It is also known as the Gaussian or standard
normal distribution, is the <span>probability
distribution<span> that plots all of its values in an
even fashion, and most of the results are positioned around the probability's
mean. Values are equally likely to plot either above or below the mean. And the
second answer is letter d - sampling distribution. In statistics, it is the
probability distribution of a given statistic centered on a
random sample. Sampling distributions are significant
in statistics because they deliver a major simplification to the statistical
inference.</span></span>