0.45 as a fraction is
45/100 and in simplest form it is
9/20.
Answer:
Solution-
We know that,
Residual value = Given value - Predicted value
The table for residual values is shown below,
Plotting a graph, by taking the residual values on ordinate and values of given x on abscissa, a random pattern is obtained where the points are evenly distributed about x-axis.
We know that,
If the points in a residual plot are randomly dispersed around the horizontal or x-axis, a linear regression model is appropriate for the data. Otherwise, a non-linear model is more appropriate.
As, in this case the points are distributed randomly around x-axis, so the residual plot show that the line of regression is best fit for the data set.
Hope this helps!
Step-by-step explanation:
9514 1404 393
Answer:
Step-by-step explanation:
The slope formula is useful for this.
m = (y2 -y1)/(x2 -x1)
__
<u>First line</u>:
m = (-9 -(-9))/(9 -(-6)) = 0/15 = 0
The slope of the first line is zero.
__
<u>Second line</u>:
m = (-5-1)/(4 -4) = -6/0 = undefined
The slope of the second line is undefined.
_____
It is always a good idea to apply a little critical thinking to the given information. Here, you observe that the y-coordinates of the first pair of points are the same. That means this is a horizontal line, with a slope of 0.
Similarly, you observe that the x-coordinates of the second pair of points are the same. That means this is a vertical line, with undefined slope.
The answer is C that is X=7 and X=-1
multiple x through the given equation to get rid of a fraction. It will be
After that bring 6X to the LHS of the equation
so that it will look like the general equation that is
Use the quadratic formula (or any other approach to find the values of x
You will arrive at
Answer:
See the proof below
Step-by-step explanation:
Let the line AB be a straight line on the parallelogram.
A dissection of the line (using the perpendicular line X) gives:
AY ≅ BX
Another way will be using the angles.
The angles are equal - vertically opposite angles
Hence the line AY ≅ BX (Proved)
