Autocorrelation is most likely to be a problem in which research design?
Time-series design.
Autocorrelation arises when repeated measurements on the same participants are not independent, a core feature of time-series data.
Measuring anxiety on five consecutive days before and after an intervention exemplifies what design?
Time-series design.
Repeated measures before and after an intervention track trends over time within the same subjects.
If standard deviations differ across groups in a t-test, when is this least problematic?
When sample sizes are equal.
Equal group sizes reduce bias caused by violating homogeneity of variance.
What does squaring the multiple correlation coefficient (R) yield?
Shared variability among three or more variables.
R² indicates the proportion of variance in the criterion explained jointly by all predictors.
An ABAB single-subject design primarily controls which threat to internal validity?
History effects.
Replication of treatment and withdrawal helps confirm that changes stem from the intervention, not external events.
About 15% of GPA variance is explained by study time. What is the correlation (r)?
r ≈ .39.
Because r² = .15 → r = √.15 ≈ .39.
In what design do participants act as their own no-treatment controls?
Single-subject design.
Each participant’s baseline (A) data serve as their control condition.
What is the main purpose of ANCOVA?
To statistically remove the effect of an extraneous variable (covariate).
This clarifies the true effect of the independent variable on the dependent variable.
Comparing pre- and post-intervention means from the same participants requires which test?
t-test for dependent (correlated) samples.
Used when the same individuals provide both sets of scores.
In a multiple-baseline design, how is treatment applied?
Sequentially to different behaviors, settings, or participants.
Helps establish causality without withdrawing treatment.
Adding 10 points to every score affects which statistic?
The mean only.
Adding a constant shifts the distribution’s central tendency but not its variability.
What happens when Pearson r is used on a curvilinear relationship?
It underestimates the true relationship.
Pearson assumes linearity; nonlinear data reduce r’s magnitude.
Which behavioral recording method best measures time on-task?
Interval recording.
Used for behaviors without a clear beginning or end.
Trend analysis is used when the independent variable is:
Quantitative.
It evaluates linear or nonlinear trends (e.g., quadratic) across ordered values.
When is the correlation between X and Y approximately zero?
When the range of Y at each X equals the total range of Y.
Indicates no consistent relation—scatterplot appears rectangular.
What procedure best reduces experimenter expectancy bias?
Double-blind design.
Both participant and experimenter remain unaware of condition assignments.
In a normal curve, about what percent of scores fall between the mean and +1 SD?
34%.
Roughly two-thirds (68%) lie within ±1 SD; half of that (34%) lies on each side.
To test a causal model’s fit among variables, use:
Path analysis (structural equation modeling).
Evaluates whether sample data match a hypothesized causal structure.
Which correlation method suits gender (dichotomous) and reaction time (ratio)?
Point-biserial correlation.
One dichotomous variable and one continuous variable.
When adding a constant to each score, how is variability affected?
Unchanged.
Range, SD, and variance remain constant; only the mean shifts.
Which statistic measures the proportion of variance in Y explained by X?
Coefficient of determination (r²).
Shows shared variance between predictor and criterion.
What is the most suitable measure of central tendency when outliers exist?
Median.
Less sensitive to extreme or estimated values.
Which observation method measures if a behavior occurred during fixed time intervals?
Interval recording.
Records presence/absence within predefined time blocks.
What happens if you use Pearson r when anxiety and performance are curvilinear?
r underestimates the strength of the relationship.
A quadratic (inverted-U) relation violates linearity assumption.
