Step by Step
D
Direction
State whether the relationship is positive (as one variable increases, so does the other) or negative (as one increases, the other decreases).
U
Unusual points
Note any outliers or influential points that deviate noticeably from the overall pattern.
F
Form
Describe the overall shape of the relationship: linear or curved (nonlinear).
U/S
Unusual clusters and Strength
Note any distinct clusters or groupings in the data, and describe the overall strength of the relationship (strong, moderate, or weak) based on how closely the points follow the pattern.
Applied Walkthrough
1
A scatterplot shows study hours (x-axis) versus exam scores (y-axis) for a group of students.
2
Direction: positive — more study hours are associated with higher exam scores.
3
Form: the relationship looks roughly linear. Strength: the points cluster closely around a line, suggesting a strong relationship.
4
Unusual points: one student studied very little but scored very high — this point is an outlier relative to the overall pattern and should be specifically called out, referencing the actual variables in context ("study hours" and "exam scores"), not just abstractly as "x" and "y."
Exam Application
Exams test whether you address all five DUFUS components when describing a scatterplot, and specifically whether you reference the actual variables in context rather than generic "x" and "y" language.
⚠ Common Trap
The most common trap is describing only direction and strength while forgetting to mention form, unusual points, or clusters — a complete scatterplot description requires all five DUFUS components, referenced using the actual variable names.
✓ Quick Self-Check
1. What does the DUFUS mnemonic stand for?
Direction, Unusual points, Form, Unusual clusters, Strength.
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2. What are the two possible directions of a relationship in a scatterplot?
Positive or negative.
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3. What does "form" describe in a scatterplot?
Whether the relationship is linear or curved (nonlinear).
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4. Why is it important to reference the actual variables in context when describing a scatterplot?
Because a complete, exam-worthy description ties the pattern to what the variables actually represent, not just abstract "x" and "y" language.
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5. What determines the "strength" of a relationship in a scatterplot?
How closely the points cluster around the overall pattern — strong, moderate, or weak.
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