## Lesson 3: Linear Regression

January 24, 2017

Tue, Jan 24

Review:

- Pearson Correlation Coefficient

Presentation:

- Linear regression
- Calculate equation of the regression line
- y-hat = b1*x + bo
- b1 = “slope” of the line
- b0 = “y-intercept”

- b1 = SSxy/SSxx
- b0 = (∑y/n) – b1*(∑x/n)

- y-hat = b1*x + bo
- Examples
- Beer party data: {(60,10), (70,12), (80,20), (90,40)}
- Calculate slope (b1) and y-intercept (b0) for linear equation
- Solve for each “x” value (i.e., plug in 60, 70…and solve for y) to produce corresponding “y-hat” values

- Calculate equation of the regression line

Activity:

- Calculate Linear Regression Equations
- Use calculations from previous class
- Data set 1: {(3,5), (5,8), (8,11), (12,10)}
- Data set 2: {(50,12), (60,15), (70,20), (80,30)}
- Data set 3: {(2,12), (4,9), (7,6), (11,3)}

- Use calculations from previous class
- Use linear equations to calculate “y-hat” values
- Add a new column to each data table for “y-hat” values