2. 5.7 – Predicting with Linear Models

3.  Today we will be learning how to: ◦ Determine whether a linear model is appropriate ◦ Use a linear model to make a real-life prediction

4.  Modeling real-life situations is a major goal for this course  Today we will decide whether a linear model can be used to represent real-life data

5.  Example 1  The manager of a restaurant made the following table.  Which data are better modeled by a linear model? Average Price Per Pound ($) YearFishMeat 19913.752.50 19934.252.70 19955.253.00 19976.753.30 19998.753.50

6.  Example 2  Write a linear model for the average meat prices given in Example 1. Average Price Per Pound ($) YearFishMeat 19913.752.50 19934.252.70 19955.253.00 19976.753.30 19998.753.50

7.  Linear interpolation – method of estimating the coordinates of a point that lies between two given data points  Linear extrapolation – method of estimating the coordinates of a point that lies to the right of left of all of the given data points

8.  Example 3 ◦ Use the linear model from Example 2 to estimate the average price per pound of meat in the given year. Tell whether you use linear interpolation or linear extrapolation.  2002  1998

9. HOMEWORK Page 319 #11-22 all #25 – 34