AP Statistics Flashcards: Residuals
Written by AP Content Team, Verified for 2026 AP Exams, Last updated: May 2026
Review key ideas with interactive flashcards. This set includes 11 cards to help you master important concepts.
What is the primary purpose of using a residual plot?
Residual plots can be used to investigate the appropriateness of a selected model.
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What is the primary purpose of using a residual plot?
Residual plots can be used to investigate the appropriateness of a selected model.
What is a residual?
A residual is the difference between the actual value (y) and the predicted value (y-hat).
What does apparent randomness in a residual plot suggest about a linear model?
Apparent randomness in a residual plot for a linear model suggests a linear form of association is appropriate for the data.
Define a residual plot.
A residual plot is a plot of residuals versus explanatory variable values or predicted response values.
How do residual plots help describe bivariate data?
Residual plots can be used to describe the form of association of bivariate data.
How would you use a residual plot to check if a linear model is a good fit?
You would examine the residual plot for apparent randomness, which suggests the linear model is appropriate.
If a student wants to determine if a linear model is appropriate for their data, what should they create and analyze?
The student should create a residual plot and analyze it to investigate the appropriateness of the selected linear model.
What is the formula for a residual?
The formula is the difference between the actual and predicted value: residual = y - y-hat.
What is plotted on the y-axis of a residual plot?
The residual values (y - y-hat) are plotted on the y-axis.
What do the points on a residual plot represent?
The points on a residual plot represent the differences between the measured and predicted responses for each data point.
What are the two possible variables for the x-axis of a residual plot?
The x-axis of a residual plot can show either the explanatory variable values or the predicted response values.