Welcome to Algebra 2!

1. Welcome to Algebra 2! • Get out your homework • Get out catalogs • Get out writing utensils • Put bags on the floor • Be quiet!!! 2-7: Curve Fitting with Linear Models

2. Curve Fitting with Linear Models Section 2-7 2-7: Curve Fitting with Linear Models

3. Definitions • Regression is the statistical study of the relationship between sets of data • Scatterplot is a graph that helps understand the form, direction, and strength of the relation; individual points • Correlation is the strength and direction of the linear relationship between two variables • Correlation Coefficient is the measure of how well the data set is fit by through a model; represented by r • -1 ≤ r ≤ 1 • Line of Best Fit is the line that best approximates a set of data 2-7: Curve Fitting with Linear Models

4. Steps of Curve Fitting • Identify and list all of the data points • Put data into calculator – use STAT key • STAT  CALC  and select LinReg (ax + b) to get the equation 2-7: Curve Fitting with Linear Models

5. Example 1 The table shows the U.S. daily oil production y (in thousands of barrels x years) after 1994. • Use the graphing calculator to find and graph the equation of the best-fitting line. • Use the equation from part (a) to predict the daily oil production in 2009. 2-7: Curve Fitting with Linear Models

6. Your Turn Use the graphing calculator to find and graph the equation of the best-fitting line. 2-7: Curve Fitting with Linear Models

7. Assignment A2-2 • P. 146: #1, 3, 5 + 9, 10, 11 2-7: Curve Fitting with Linear Models

8. Assignment A2-4 A2-6 • P. 146: #1, 3, 5 2-7: Curve Fitting with Linear Models