Answer:
-32.4
Step-by-step explanation:
-1.2/(-0.4) = 3
-3.6/(-1.2) = 3
-10.8/(-3.6) = 3
Each new terms is the previous term multiplied by 3.
-10.8 * 3 = -32.4
Answer:
4.7/5
Step-by-step explanation:
Answer:
a) WS, ZV, YU
b) VU
c) ZW
d) WXY
e) None
f) TU, TV, UV, XY, XZ, YZ
g) SW, VX, VZ, WX, WZ, YZ
Step-by-step explanation:
A prism is a polyhedron that has:
- Two bases that are congruent and parallel to each other.
- Lateral sides that are parallelograms and link the two bases.
- Height that is the distance between the two bases.
From inspection of the give diagram, the figure appears to be a quadrilateral prism with bases STUV and WXYZ.
<u>Parallel line segments</u>
- Parallel line segments lie on parallel lines.
- Parallel lines are lines on a plane that <u>never meet</u> and are the <u>same distance apart</u>.
a) Segments parallel to XT:
b) Segments parallel to ZY:
c) Segments parallel to VS:
<u>Planes</u>
- A plane is a flat, two-dimensional surface that extends into infinity.
- A plane can be named by the letters naming three non-collinear points in the plane.
- Parallel planes are planes that never intersect.
d) Planes parallel to plane STU:
e) Planes parallel to plane UVZ:
<u>Skew lines</u>
Skew lines are a pair of non-coplanar lines that:
- Do <u>not</u> intersect.
- Are <u>not</u> parallel to each other.
f) Segments skew to SW:
g) Segments skew to UT:

<h2>
Explanation:</h2>
The slope-intercept form of the equation of a line:

The given line has the following characteristics:

So the line we are looking for needs to be:

So, the equation of the line would be:

<h2>Learn more:</h2>
Many-to-one function: brainly.com/question/12881881
#LearnWithBrainly
Answer:
y = 0.28X - 0.77
Step-by-step explanation:
Given the data :
X:
40
32
38
21
у:
10
8
10
5
Equation of regression line is in the form:
y = mx + c
Where y = predicted variable ;
c = intercept ; m = slope or gradient ; x = predictor variable
Using The correlation Coefficient calculator :
The regression equation obtained is :
ŷ = 0.2754X - 0.77028
Rounding values in our regression output to 2 decimal places :
y = 0.28X - 0.77
Hence best model to make prediction :
y = 0.28X - 0.77