Answer:
see below
Step-by-step explanation:
The first equation is in slope-intercept form, so you can see that the boundary line has a slope of -2 and goes through the point (x, y) = (0, -4). Since the comparison is "<", the line is dashed and shading is below it.
The second equation is that of a vertical boundary line at x=-3. It is solid, because the comparison includes the "equal" case. Shading is to the right of it, where x values are greater than -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).
Answer:
$16,000 should be invested in the 4.25% bond
Step-by-step explanation:
Attached is the full solution
