With a line of best fit already drawn, use two marked points on the line to find its slope; the scattered dots need not sit exactly on the model. A new vertical intercept occurs where the new input is zero, so translate that zero back to the old input before making a prediction. Apply the new output rule last, or you'll find an intercept for the wrong input.
Hints
- Hint 1
The open circles lie on the fitted line, so use them to find how much changes when increases. The solid dots are measurements and don't have to lie exactly on that line.
- Hint 2
A vertical intercept has a horizontal coordinate of zero. Here the new horizontal coordinate is , not . What value of makes equal zero?
- Hint 3
Start at a marked point on the line and use its slope to predict at that old value. Then follow the parentheses in : subtract before multiplying by .
Step-by-step
Find the old prediction at the new intercept
Step 1Find the fitted line's slope
The open circles and are on the fitted line, unlike the solid measurement dots. The slope is the change in divided by the change in . Type in Desmos; it shows . So the fitted line predicts fewer hour for each increase of in .
- Step 2
Find the old input where the new input is zero
The -intercept is where , so becomes . Type in Desmos; tells it to find the value that makes both sides match. Under PARAMETERS, Desmos shows . Set the new input to zero, then translate it back to the old input.
- Step 3
Predict the old output
Use the point on the line. Starting at , a change of changes the predicted time by , so . Type below the regression; Desmos uses its fitted and shows hours. Using instead would predict the old intercept, not the one asked for.
- Step 4
Convert the prediction to the new output
Apply the new output rule to the predicted . Type ; Desmos shows . The same transformations carry the fitted line along with the data, so this is the value where : the new line's -intercept. Choice C.