Lesson 3

1. Lesson 3

1.10. Explore 6

Mathematics 30-2 Module 4

Module 4: Polynomials

 

In Try This 3, you saw that the cubic regression equation sometimes predicts unrealistic values and that you need to be careful when using a model to make predictions. Typically, interpolation (predicting a value within the data) is much more reliable than extrapolation (predicting a value outside the data).

 

Just as in the egg example, you may have noticed that solving the equation 3 = −0.0014x3 + 0.064x2 − 0.6399x + 11.7298 can be done by graphing both sides of the equation and finding the intersection.

 

This shows a scatter plot with a curve of best fit superimposed. There is also a horizontal line at y = 3. The x-axis is labelled “Years Since 1970” and the y-axis is labelled “Births (thousands).” The  horizontal line intersects the curve of best fit at the point (35.1896, 3).
The graphs of y = −0.0014x3 + 0.064x2 − 0.6399x + 11.7298 and
y
= 3 intersect at (35.1896, 3). Therefore, 35.1896 is a solution to the equation 3 = −0.0014x3 + 0.064x2 − 0.6399x + 11.7298.


textbook

Read “Example 2” on pages 310 to 312 of your textbook to see how a cubic regression can be used to model data. Pay attention to how Brad determines the year gas prices were 56.0¢/L.

 

Self-Check 3

 

Complete questions 2, 5, and 9 on pages 313 to 315 of your textbook. Answers