The answer
the table is
x 0 1 4 5 7
y 3 1 0 -2 -2
<span>the approximate line of best fit to be y = –0.7x + 2.36
so when the value of x=5, the residual value is
</span><span>y = –0.7(5) + 2.36 = -1.14 this is the actual value
the predicted value is -2 (for x=5)
and residual value formula is RS = y actual value - y predicted value
so RS = -1.14 - (-2) = 0.86
</span>
The answer is that his average is 75.5 for the second nine weeks
The domain is the x values
y = 2 - x
when x = -3
y = 2 - (-3)
y = 2 + 3
y = 5....so ur points are (-3,5)
when x = -2
y = 2 - (-2)
y = 2 + 2
y = 4....so ur points are (-2,4)
when x = -1
y = 2 - (-1)
y = 2 + 1
y = 3...so ur points are (-1,3)
when x = 0
y = 2 - 0
y = 2....so ur points are (0,2)
when x = 1
y = 2 - 1
y = 1...so ur point are (1,1)
so basically, u plot all of those points
Answer:

Step-by-step explanation:
Using right estimation point simply means to form a bunch of rectangles between the two limits, x =2 and x = 5. and add the areas of all those rectangles.
There must be 6 subdivisions between 2 and 5. so, to do that:

the length of each subdivision is 0.5 units. That also means that the 6 rectangles in between the limits will each have the base length of 0.5 units.
So the endpoints of each subdivision from 3 to 5 will be:

By <em>right </em>endpoint approx<em>, </em>we mean that the height of the rectangles will be determined by the right endpoint of each subdivision, that is, it must be equal to the function value of the first limit.

Note that we have used the right-end-point of the subdivision to determine the height the rectangles.
All that's left to do now is to simply calculate the areas of the each of the rectangles. And add them up.
the base of each of the rectangle is 
and the height is determined in the table above.



Answer:
Step-by-step explanation: