Chapter 8-Linear Regression

Chapter 8-Linear Regression

1. Model

   • An equation or formula that simplifies and represents reality.

2. Linear model

   • A linear model is an equation of a line. To interpret a linear model, we need to know the vari- ables (along with their W’s) and their units.

3. Predicted value

   • The value of found for a given x-value in the data. A predicted value is found by substituting the x-value in the regression equation.

4. Residuals

   • Residual = observed value - predicted value = e = y - y

5. Least squares

   • specifies the unique line that minimizes the variance of the residuals or, equivalently, the sum of the squared residuals.

6. Line of best fit

   • N = b0 + b1x