Answer:
The sum of the squared residuals
Step-by-step explanation:
If you sum the residuals, you would get 0
if you sum of the absolute values of the residuals you wouldn't be doing "least-squares regression"
The influence of outliers D The slope is another metric that has nothing to do in creating the regression line
Answer:
A. Increase by 2
Step-by-step explanation:
Given that a fitted multiple regression equation is

This is a multiple regression line with dependent variable y and independent variables x1, x2, x3 and x4
The coefficients of independent variables represent the slope.
In other words the coefficients represent the rate of change of y when xi is changed by 1 unit.
Given that x3 and x4 remain unchanged and x1 increases by 2 and x2 by 2 units
Since slope of x1 is 5, we find for one unit change in x1 we can have 5 units change in y
i.e. for 2 units change in x1, we expect 10 units change in Y
Similarly for 2 units change in x2, we expect -2(4) units change in Y
Put together we have
change in y
Since positive 2, there is an increase by 2
A. Increase by 2
Answer:
The answer is 1 over 5
Step-by-step explanation:
10 divided by 5 equals 2. That is your width. The same rule applies to your height. So you would get 10 over 50 which simplif equals 1 over 5.
The y intercept is -2, but I don't remember how to find the vertex sorry