Y - 3 = -2(x+5)
y - 3 = -2x - 10
+3. +3
y = -2x - 7
Answer:
4
Step-by-step explanation:
<h3>2^3= 2x2x2= 8 + 4 =12</h3><h3 /><h3>but it is 16 not 12 so 16 - 12 =4 so that should be ur awnser.</h3><h3 /><h3 /><h3 /><h3>In return can u answer the question that i just asked on my account</h3>
Answer:
3
Step-by-step explanation:
Given a line with points; (2, 5) (3, 8).
1. Find the slope of the given line
The formula for finding the slope is:

Substitute in the values;


simplify;

= 3
2. Find the slope of the parallel line;
Remember, when two lines are parallel, they run alongside each other, of infinitely long, but they never touch. Hence two parallel lines have the same slope. Therefore, the slope of a line that is parallel to the given one will also have the same slope as the given one, which is 3.
Answer:
II. The sum of the residuals is always 0.
Step-by-step explanation:
A least squares regression line is a standard technique in regression analysis used to make the vertical distance obtained from the data points running to the regression line to become very minimal or as small as possible.
For any least-squares regression line, the sum of the residuals is always zero.
Basically, residuals are used to measure or determine whether or not the line of regression is a good fit or match for the data by subtracting the difference between them i.e the predicted y value and the actual y value, for the x value respectively.
Hence, the statement about residuals which is true for the least-squares regression line is that the sum of the residuals is always zero (0).