Understanding Linear Regression

Front

Linear Regression

Back

A statistical method to model the relationship between a dependent variable and one or more independent variables.

Front

Response Variable

Back

The dependent/ outcome variable that the model aims to predict, displayed on the y-axis

Front

Explanatory Variable

Back

The input variable (x) , independent variable , used to predict the dependent variable.

Front

Linear Regression Equation

Back

y-hat = a + bx

Front

the initial predicted value when x = 0

Back

Y-intercept of the regression line.

Front

For every 1 additional x increment, what is predicted to happen to the response variable.

Back

Slope of the regression line.

Front

ε

Back

Error term in the regression equation.

Front

Least Squares Method

Back

Technique to minimize the sum of squared residuals.

Front

Residual

Back

Difference between observed and predicted values.

Front

Coefficient of Determination

Back

R², measures the goodness of fit.