Use the graphing calculator tool to plot the residual points.

(1, 0.86), (2, –0.25), (3, –1.66), (4, –2.34), (5, –4.1)

does the residual plot show that the line of best fit is appropriate for the data?

yes, the points have no pattern.
yes, the points are evenly distributed about the x-axis.
no, the points are in a linear pattern.
no, the points are in a curved pattern.

The correct answer is:

No, the points are in a linear pattern.

Explanation:

A residual is the difference between a value predicted by a regression line and the actual data point. A residual plot is a scatter plot of these, where the y-axis is the residual value and the x-axis is the independent value.

A residual plot does not have a predictive value. This means if the regression is a good fit, the residual plot should be scattered, without a pattern. If your residual plot has a pattern such that you can predict residual values that aren’t showing, your regression is not a good fit.

In this residual plot, the points appear to form a line. It is a fairly strong linear pattern. This means the regression is not a good fit.

No, the points are in a linear pattern.

Step-by-step explanation:

Hope This helps!

the value of v.w= -12.

step-by-step explanation:

we are given three vector r,v and w as:

r = < 5, -5, -2> ; v = < 2, -8, -8> ; w = < -2, 6, -5>

we know that r,v and w could also be represented as:

r=5i-5j-2k

v=2i-8j-8k

and w= -2i+6j-5k

where i,j and k are the unit vectors of x,y and z-axis respectively.

also we know that it has the following property:

i.i=1 ; j.j=1; k.k=1

and i.=j.i=i.k=k.i=j.k=k.j=0

i.e. when we multiply two vectors or we find it's dot product we need to only multiply the components of x coordinates with each other; y with each other and z with each other.

hence, v.w= (2i-8j- -2i+6j-5k)

                  = 2×(-2)+(-8)×(6)+(-8)×(-5)

                  = -4-48+40

                  = -12

hence, v.w= -12

45

step-by-step explanation: