1. OBJECTIVES 2-2 LINEAR REGRESSION
Banking
4/19/2017
2-2 LINEAR REGRESSION
OBJECTIVES
Be able to fit a regression line to a scatterplot.
Find and interpret correlation coefficients.
Make predictions based on lines of best fit.
Chapter 1

2. Key Terms line of best fit linear regression line least squares line
domain
range
interpolation
extrapolation
correlation coefficient
strong correlation
weak correlation
moderate correlation

3. Example 1
Find the equation of the linear regression line for Rachael’s scatterplot in Example 1 from Lesson 2-1. Round the slope and y-intercept to the nearest hundredth. The points are given below.
(65, 102), (71, 133), (79, 144), (80, 161), (86, 191),
(86, 207), (91, 235), (95, 237), (100, 243)

4. Example 2
Interpret the slope as a rate for Rachael’s linear regression line. Use the equation from Example 1.

5. CHECK YOUR UNDERSTANDING
Approximately how many more water bottles will Rachael sell if the temperature increases 2 degrees?

6. EXAMPLE 3
How many water bottles should Rachael pack if the temperature forecasted were 83 degrees? Is this an example of interpolation or extrapolation? Round to the nearest integer.

7. EXAMPLE 4
Find the correlation coefficient to the nearest hundredth for the linear regression for Rachael’s data. Interpret the correlation coefficient.

8. CHECK YOUR UNDERSTANDING
Find the equation of the linear regression line of the scatterplot defined by these points: (1, 56), (2, 45), (4, 20), (3, 30), and (5, 9). Round the slope and y-intercept to the nearest hundredth.
Find the correlation coefficient to the nearest thousandth. Interpret the correlation coefficient.

9. EXTEND YOUR UNDERSTANDING
Carlos entered data into his calculator and found a correlation coefficient of Interpret this correlation coefficient.