Scatter Plot AnalysisComplete Guide
Identify when behaviors occur by mapping patterns across time and days. Essential for FBAs and intervention planning.
What is Scatter Plot Analysis?
Scatter plot analysis (also called scatterplot assessment) is a data collection method that creates a visual map of when behaviors occur. By recording behavior occurrence across time intervals and days, scatter plots reveal temporal patterns that help identify environmental triggers and inform intervention strategies.
Why Use Scatter Plots?
Reveals Time Patterns
See at a glance which time periods have highest behavior occurrence
Identifies Triggers
Connect patterns to activities, transitions, or environmental factors
Guides FBA
Focus ABC data collection on high-occurrence times for efficiency
Monitors Intervention
Track changes in behavior patterns after implementing supports
Sample Scatter Plot
This example shows a student with elevated behaviors during math, writing, and transitions. Notice the clear horizontal pattern during specific activities.
Student: Example Student
Target Behavior: Off-task behavior (out of seat, not engaging with materials)
| Time | Activity | Mon | Tue | Wed | Thu | Fri |
|---|---|---|---|---|---|---|
| 8:00-8:30 | Arrival | |||||
| 8:30-9:00 | Morning Work | |||||
| 9:00-9:30 | Reading | |||||
| 9:30-10:00 | Math | |||||
| 10:00-10:30 | Recess | |||||
| 10:30-11:00 | Science | |||||
| 11:00-11:30 | Lunch | |||||
| 11:30-12:00 | Lunch | |||||
| 12:00-12:30 | Specials | |||||
| 12:30-1:00 | Writing | |||||
| 1:00-1:30 | Social Studies | |||||
| 1:30-2:00 | Centers | |||||
| 2:00-2:30 | Pack Up | |||||
| 2:30-3:00 | Dismissal |
High-Occurrence Patterns
- • Math (9:30-10:00): High every day - possible escape-maintained
- • Writing (1:30-2:00): High 4/5 days - academic demand pattern
Moderate Patterns
- • After Lunch (12:30-1:00): Elevated - transition/sensory
- • Pack Up (2:30-3:00): Elevated - end-of-day transition
How to Create a Scatter Plot
Set Up Your Grid
Create a table with time intervals as rows and days/dates as columns.
- →Use consistent time intervals (15, 30, or 60 minutes)
- →Include at least 2 weeks of columns
- →Add an "Activity" column for context
Define Your Coding System
Decide how you will mark behavior occurrence in each cell.
- →Simple: occurred vs. did not occur
- →Detailed: none, low (1-2), high (3+)
- →Use colors or symbols consistently
Collect Data Daily
At the end of each time interval, mark whether behavior occurred.
- →Set reminders for consistent recording
- →Use "not observed" code when absent
- →Digital tools can automate this process
Look for Patterns
After 2+ weeks, analyze the visual data for clusters and trends.
- →Horizontal clusters = time-based patterns
- →Vertical clusters = day-specific patterns
- →Random distribution = multiple variables
Cross-Reference with Schedule
Connect high-occurrence times to activities, staff, and environmental variables.
- →What activity occurs during high times?
- →Are certain staff present or absent?
- →What happens right before high-occurrence periods?
Develop Hypotheses
Use patterns to form educated guesses about behavior function.
- →High during academic demands → escape?
- →High after lunch/recess → sensory/regulation?
- →High during unstructured time → attention?
Interpreting Scatter Plot Patterns
Horizontal Pattern
Same time period shows high occurrence across multiple days.
Possible Interpretations:
- • Specific activity is triggering
- • Environmental variable at that time
- • Schedule-related antecedent
Vertical Pattern
One specific day shows elevated behavior throughout.
Possible Interpretations:
- • Specific staff on that day
- • Weekly schedule variation
- • External factors (sleep, medication)
Scattered Pattern
No clear pattern; behavior appears random.
Possible Interpretations:
- • Multiple maintaining variables
- • Need longer observation period
- • Internal/sensory function
No Occurrence
Target behavior did not occur during observation period.
Consider:
- • Is the operational definition accurate?
- • Is the behavior truly low-frequency?
- • Were observations during typical times?
Frequently Asked Questions
What is a scatter plot in behavior analysis?
A scatter plot (also called scatterplot assessment) is a data collection tool that maps when behaviors occur across time periods and days. It creates a visual grid showing patterns of behavior occurrence, helping identify times of day or specific conditions when behaviors are most likely to happen.
How do I read a behavior scatter plot?
Read a scatter plot by looking for clusters of marked cells. Horizontal patterns (same time each day) suggest time-based triggers like transitions or activities. Vertical patterns (throughout certain days) may indicate day-specific factors. Diagonal or random patterns suggest variable triggers.
How long should I collect scatter plot data?
Collect scatter plot data for a minimum of 2 weeks (10 school days) to identify reliable patterns. Some behaviors may require longer observation periods (3-4 weeks) to capture weekly variations or less frequent patterns.
What time intervals should I use for scatter plots?
Choose intervals based on your schedule and behavior frequency. 30-minute intervals work well for most school settings. Use 15-minute intervals for high-frequency behaviors or detailed analysis. 60-minute intervals may be appropriate for low-frequency behaviors.
How is a scatter plot different from ABC data?
Scatter plots show WHEN behaviors occur without recording what happens before or after. ABC data captures the specific Antecedent-Behavior-Consequence for each incident. Use scatter plots to identify patterns, then ABC data to understand function during high-occurrence times.
Can scatter plots identify behavior function?
Scatter plots alone do not directly identify function, but they provide strong clues. Patterns of occurrence during specific activities, transitions, or times help form hypotheses about function that can be tested with ABC data or functional analysis.
What do I do if I see no clear pattern in my scatter plot?
If no clear pattern emerges: (1) collect data for a longer period, (2) use smaller time intervals, (3) check if your operational definition is consistent, (4) consider if the behavior is truly variable and may be maintained by multiple functions.
How do I code a scatter plot?
Common coding systems include: filled circle/dark shading for behavior occurred, empty circle/no shading for behavior did not occur, slash or X for time not observed. Some practitioners use three levels: high (filled), low (half), none (empty).
Create Digital Scatter Plots
Classroom Pulse automatically generates scatter plots from your behavior data. No manual charting required.