Linear Regression Models and Residuals

Front

What is a residual plot?

Back

A graphical representation that shows the residuals on the vertical axis and the independent variable on the horizontal axis, used to assess the fit of a regression model.

Front

What should a residual plot look like for a good linear regression model?

Back

A good residual plot should show no distinct pattern and appear random.

Front

What does the linear regression equation y = 61.93x - 1.79 represent?

Back

It represents a linear relationship between the independent variable x and the dependent variable y, where 61.93 is the slope and -1.79 is the y-intercept.

Front

How do you predict values using a linear regression equation?

Back

Substitute the value of the independent variable into the equation to calculate the predicted value of the dependent variable.

Front

What does the slope of a linear regression model indicate?

Back

The slope indicates the change in the dependent variable for each one-unit increase in the independent variable.

Front

What are residuals in the context of linear regression?

Back

Residuals are the differences between the observed values and the values predicted by the regression model.

Front

What does it mean if residuals are randomly distributed?

Back

It indicates that the linear regression model is appropriate for the data.

Front

What is the significance of the y-intercept in a linear regression equation?

Back

The y-intercept represents the predicted value of the dependent variable when the independent variable is zero.

Front

How can you interpret the slope of the equation y = 61.93x - 1.79?

Back

The slope of 61.93 means that for every hour of driving, the distance traveled increases by 61.93 miles.

Front

What does a non-random pattern in a residual plot suggest?

Back

It suggests that the linear regression model may not be the best fit for the data.