Section 2.6 Flashcards
One quantitative variable: Regression Line Predicted Values Residuals Interpreting slope and intercept Cautions (8 cards)
Regression Line
The straight line that best fits the data in a scatterplot
Estimated Equation of the Regression Line
y-hat = a+bx
(y-hat = predicted response)
(x = explanatory)
Observed Response Value
The response value observed for a particular data point
Predicted Response Value
The response value that would be predicted for a given X value, based on a model
(The best fitting line is that which makes the predicted values closest to the actual values)
Residual
The Residual for each data point is observed - predicted = y - y-hat
(The residual is also the vertical distance from each point to the line)
Least Square Line
The line which minimizes the sum of squared residuals
Slope
Increase in predicted y for every unit increase in X
Intercept
Predicted Y value when X = 0