Interpreting the Slope and Y Intercept of Linear Regression

These flashcards cover key vocabulary and concepts related to interpreting the slope and y intercept of a linear regression model.

Slope

The value that represents the change in the predicted response variable for each one unit increase in the explanatory variable.

Y Intercept

The predicted value of the response variable when the explanatory variable is equal to zero.

Interpretation of Slope

For every one unit increase in the explanatory variable, the model predicts an average increase (or decrease) in the response variable based on the slope value.

Meaningful Y Intercept

A y intercept is meaningful in context only if the explanatory variable can reasonably be zero.

Least Squares Regression Line Equation

y hat = a + b x, where 'a' is the y intercept and 'b' is the slope.

Negative Y Intercept Interpretation

A negative predicted value for the response variable that is illogical in certain contexts, such as predicting scores for zero attendance.

Coefficient

A numerical value that represents the relationship between an explanatory variable and the response variable in regression.

Explanatory Variable

The independent variable that is used to predict the value of the response variable.

Response Variable

The dependent variable that is being predicted in a regression model.

Predicted Value

The value generated by the model based on the regression equation for given values of the explanatory variable.