From Scatterplot Skills to a Free-Response Answer
In “Describing a Scatterplot With DUFS,” you learned to organize a description around direction, unusual features, form, and strength. In “Writing Descriptions in Context,” you practiced naming the individuals, variables, and units. Now the task is to bring those skills together in the concise, complete response an AP-style question calls for—and to judge whether an answer actually earns credit.
A scatterplot description is not a list of adjectives. A strong answer connects the pattern to the situation, distinguishes the overall pattern from any unusual features, and avoids claiming more than the graph supports. The practice rubric in this tutorial is designed for learning; it is not an official College Board scoring rubric.
A Practice Rubric for Describing a Scatterplot
For the worked examples, use this four-point practice rubric. Award one point for each feature when the response is accurate and sufficiently specific. A response can earn some points even if another part is missing or incorrect.
| Point | What a complete response does |
|---|---|
| Direction and context | Names the variables and describes how the response tends to change as the explanatory variable increases. |
| Form | Describes the overall pattern as roughly linear, curved, or another recognizable shape. |
| Strength | Describes how closely the points follow the overall pattern, using an adjective that fits the plot. |
| Unusual features | Identifies and locates important outliers, clusters, gaps, or other notable departures—or accurately notes that none are apparent. |
This rubric treats context as part of a sound direction statement: “positive” alone is less informative than naming what tends to increase with what. It also separates form from strength. A pattern can be strongly curved, for instance, without being linear.
When scoring, judge what the student actually wrote, not what they might have meant. Do not award a point for an unsupported claim merely because the sentence sounds confident. At the same time, do not require a long paragraph: a few accurate, contextual sentences can cover all four features.
Worked Example: Sunlight and a Garden Harvest
Worked Example: Sunlight and a Garden Harvest
A fictional community garden records the average hours of direct sunlight per day and the mass of vegetables harvested from each plot during one week. Each point represents one garden plot. The scatterplot has the following coordinates:
| Plot | Sunlight, hours per day | Harvest, kilograms per week |
|---|---|---|
| 1 | 2 | 4 |
| 2 | 3 | 5 |
| 3 | 4 | 7 |
| 4 | 5 | 8 |
| 5 | 6 | 9 |
| 6 | 7 | 5 |
| 7 | 8 | 12 |
| 8 | 9 | 13 |
| 9 | 10 | 15 |
| 10 | 11 | 16 |
Question: Describe the association between daily sunlight and weekly harvest for these garden plots.
Score this sample answer: “More sunlight goes with more harvest, so there is a positive association. The pattern is straight and strong. More sunlight causes a greater harvest.”
Score: 2 out of 4 points. The first sentence earns the direction-and-context point: it names both variables and describes a positive association. “Straight” earns the form point because it identifies a roughly linear pattern. The strength point is not earned: the points follow a roughly linear pattern, but the point at 7 hours and 5 kilograms is far below the rest, so “strong” overstates how closely all the points follow the pattern. The unusual feature is not mentioned, so that point is not earned. The causal claim is unsupported by a scatterplot and earns no point.
Full-credit response: “For these garden plots, there is a moderately strong, positive, roughly linear association between average daily sunlight and weekly vegetable harvest: plots with more hours of sunlight tend to have larger harvests. One plot is unusual, with 7 hours of sunlight per day but a harvest of only 5 kilograms, well below the overall pattern. The scatterplot shows an association, not proof that sunlight alone causes the differences in harvest.”
This response gives the variables and units, describes the overall direction and form, calibrates strength, and locates the unusual point using both coordinates. The final sentence avoids treating association as proof of cause. The answer is specific without claiming that the plot explains why the unusual harvest occurred.
Use the Rubric Without Treating It Like a Checklist
The four rubric features help you check coverage, but they are connected. The unusual point in the garden plot affects how closely the points follow the overall pattern. You should mention it separately, then choose a strength description that accounts for it. Describing the main pattern as positive and roughly linear does not mean every point must sit close to an imaginary straight line.
As in “Lurking Patterns: Time and Subgroups,” a plot may also contain groups whose patterns matter. When group labels are supplied, describe those patterns rather than treating the points as one undifferentiated cloud. The next example applies the same four rubric categories while taking group membership into account.
Worked Example: Light Exposure for Two Seedling Varieties
Worked Example: Light Exposure for Two Seedling Varieties
A fictional greenhouse compares hours of light per day with seedling height after three weeks. Points are marked by variety. In the scatterplot, both varieties show a moderately strong, roughly linear positive association. At similar light exposures, Variety B seedlings tend to be taller than Variety A seedlings. The two varieties form distinguishable clusters, and no individual point is far from its own variety’s pattern.
Question: Describe the association shown in the group-coded scatterplot.
Score this sample answer: “There is a strong positive linear association between light and height, with no unusual features.”
Score: 1 out of 4 points. “Positive” and “linear” correctly identify direction and form, but the response does not name the varieties or give the variables’ units, so it does not earn the direction-and-context point under this practice rubric. “Strong” does not match the stated moderate strength, so the strength point is not earned. The answer misses the separation between the varieties, so it does not earn the unusual-features point. Saying “no unusual features” is inaccurate when the clusters are a notable feature of the plot.
Full-credit response: “For these seedlings, height after three weeks tends to increase as daily light exposure increases, and the association is moderately strong and roughly linear for both varieties. The points form two distinguishable clusters: at similar light exposures, Variety B seedlings tend to be taller than Variety A seedlings. No individual point appears far from its variety’s pattern.”
The revised answer keeps the overall positive direction but does not let it hide the groups. It describes strength for the patterns shown and distinguishes the clusters from individual outliers. It does not claim that the variety difference was caused by light exposure; the scatterplot description alone cannot establish that.
Notice that the phrase “for both varieties” narrows the description to the patterns actually shown within the groups. Naming the clusters makes the unusual-features point specific. If the question supplied group labels, leaving them out could make an otherwise plausible pooled description incomplete.
Worked Example: A Pattern That Bends
Worked Example: A Pattern That Bends
A fictional typing program records each learner’s minutes of practice per day and typing speed in words per minute after a training period. The scatterplot shows speeds generally rising as practice time increases, but the increase slows at higher practice times. The points follow this curved pattern fairly closely, and no point stands far away from it.
Question: Describe the association between daily practice time and typing speed.
Score this sample answer: “For these learners, more daily practice is associated with higher typing speed. The relationship is strong and linear, and there are no outliers.”
Score: 3 out of 4 points. The first sentence correctly identifies the variables and positive direction, earning the direction-and-context point. “Strong” is consistent with points following the overall pattern fairly closely, so the response earns the strength point. “There are no outliers” earns the unusual-features point because the prompt says no point stands far from the pattern. However, the response calls the pattern linear when it bends, so it does not earn the form point.
Full-credit response: “For these learners, typing speed tends to increase as daily practice time increases. The association is strong and curved: typing speed rises more quickly at first and then increases more slowly at higher practice times. The points follow the curved pattern fairly closely, with no apparent outlier.”
The important revision is “curved,” followed by a description of how the curve bends. Calling the association strong does not make it linear; form and strength describe different features. The answer describes the observed pattern and does not claim that practice alone caused the speed differences.
Common Mistakes and AP Exam Tips
- Writing only a direction word. “Positive” does not tell the reader which variables are associated. Name the explanatory and response variables, and state what tends to happen to the response as the explanatory variable increases.
- Confusing form with strength. “Linear” describes a roughly straight shape; “strong” describes how closely points follow the pattern. Check both separately, especially when the pattern curves.
- Skipping unusual features. A point that is far from the main pattern can affect the description. Locate it with approximate values on both axes when those values are available.
- Calling every point far out on an axis an outlier. As in “Spotting Outliers in Bivariate Data,” judge whether a point falls far from the overall pattern, not merely whether its \(x\)- or \(y\)-value is large.
- Ignoring labeled groups. If varieties or other categories are shown, say whether the groups cluster or follow different patterns. As in “Lurking Patterns: Time and Subgroups,” a pooled description may not tell the whole story.
- Claiming cause from association. Say that the variables are associated or that one tends to increase as the other increases. Do not say one causes the other unless the study design supports a causal conclusion.
- Using a strength word that does not fit. “Strong” and “weak” are not interchangeable with “steep” and “shallow.” Judge how closely the points follow the pattern, not how sharply the pattern rises or falls.
A practical final check is to read your response as a rubric scorer would: Can you point to a specific phrase for direction and context, form, strength, and unusual features? Is each phrase accurate for this graph? Does the answer stay within what the displayed data can support? If a feature is not apparent, say so accurately rather than inventing one.
Check Your Understanding
Use the practice rubric to evaluate what a complete scatterplot description should say.
- A student writes, “The association is positive and strong.” What contextual information is missing from this statement?
- A plot has a clear U-shaped pattern, with points close to the curve. Which terms describe its form and strength?
- In the garden example, which point is unusual, and what coordinates locate it?
- Why does “there are no unusual features” fail to describe the seedling scatterplot accurately?
- Rewrite this claim cautiously: “More practice causes typing speed to increase.”