Final answer:
Single-subject designs assess significance through visual data analysis and within-subject comparisons, while group designs use statistical tests and between-group comparisons.
Step-by-step explanation:
In single-subject designs, power/significance is typically assessed using visual analysis of data trends, consistency of patterns across different phases of the experiment, and non-statistical methods that determine the reliability of observed changes (e.g., replication of effects). Unlike group designs, single-subject designs do not usually employ inferential statistics to determine significance and instead rely on within-subject comparison over time.
Group designs assess power based on the ability to reject a null-hypothesis, often using a predetermined significance level (p-value) and statistical tests like t-tests or ANOVAs, and handle larger samples allowing for analysis of variance between individuals.
Group dynamics, leadership styles, and the effect of conformity are other factors that influence both single-subject and group designs. However, the method for determining significance in traditional group studies is more systematic and quantitative compared to the qualitative nature of single-subject design assessments. In group studies, power and significance are measured by the likelihood of committing Type I errors and the sensitivity of the study to detect an actual effect.
In summary, the significant differences in assessing power between these two designs stem from the different methodologies. In single-subject designs, the emphasis is on direct and repeated observation of changes within an individual or a small sample, whereas group designs rely on statistical analyses that compare between-group differences to assess power and significance.