C.11: Interpret graphed data.
Free practice questions for this part of the BCBA, with an explanation for every option.
A BCBA graphs a child's correct mands per session. Baseline data show a steady increasing trend across 6 sessions. The BCBA then introduces an intervention, and mands keep increasing at about the same slope. Which interpretation is best supported?
- A. No clear intervention effect is shown, because the intervention data continue the baseline trend without a change in level or slope.Correct. Visual analysis compares intervention data with the baseline prediction. With no change in level, trend, or immediacy, no effect is shown.
- B. The baseline was stable, so any increase during intervention shows a functional relation.Incorrect. A clear upward trend means the baseline was not stable in the direction of the expected change.
- C. The intervention was effective, because mands increased during intervention.Incorrect. The increase was already happening in baseline, so the intervention data look like what baseline predicted.
- D. The intervention was harmful, because the slope did not get steeper.Incorrect. Mands continued to increase, which gives no evidence of harm.
After 5 baseline sessions, a client's rates of aggression range widely: 0.2, 1.8, 0.4, 2.1, and 0.3 per hour. The team is eager to start treatment. If the situation is not an emergency, what is the best next step?
- A. Start the intervention, because 5 data points is always enough.Incorrect. How many data points are needed depends on stability. Five highly variable points do not give a reliable prediction.
- B. Report the mean baseline rate of 0.96 per hour and start the intervention.Incorrect. A mean hides the variability that makes the baseline hard to interpret.
- C. Continue baseline and look for sources of the variability, because high variability makes it hard to predict future levels and to detect an intervention effect.Correct. When safety allows, extending baseline and finding variables that cause the variability makes later comparisons more convincing.
- D. Drop the high values as outliers and start the intervention.Incorrect. Removing data without a justified reason distorts the record, conflicts with honest data practices, and ignores possible controlling variables.
In a multiple baseline across behaviors, intervention is introduced for Behavior 1 at session 6. Behavior 1 improves right away. At the same session, Behavior 2, which is still in baseline, also improves markedly before its own intervention begins at session 11. How should this be interpreted?
- A. Weakened experimental control. Behavior 2 changed without intervention, which suggests the behaviors are not independent or an outside variable is involved.Correct. Covariation in an untreated tier weakens verification. It points to generalization across non-independent behaviors or to a confounding variable.
- B. Strong experimental control. Both behaviors improved, which replicates the effect.Incorrect. Replication in a multiple baseline needs each tier to change only when it receives the intervention.
- C. Strong experimental control, because Behavior 2 changed before its own intervention.Incorrect. A change before the intervention is introduced is the opposite of what demonstrates control.
- D. No interpretation is possible, because multiple baselines need at least four tiers.Incorrect. Three tiers is the usual minimum, and the problem here is the pattern of change, not the number of tiers.