Which three terms are used to visually evaluate a graph in data analysis?

The terms level, trend, and variability are fundamental concepts utilized when visually evaluating data on a graph in data analysis.

Level refers to the value or position of the data points on the y-axis at a specific point in time, which allows one to assess the overall state or magnitude of the behavior being measured.

Trend describes the direction of the data over time, indicating whether the behavior is increasing, decreasing, or remaining stable. This is crucial for understanding the changes in the data and making predictions about future performance.

Variability measures the extent of fluctuations in the data points, highlighting how consistent or inconsistent the behavior is. High variability suggests a lot of change in the data, while low variability indicates that the data points are more tightly clustered together, providing insights into predictability.

Understanding these three aspects helps behavior analysts and RBTs make informed decisions about interventions and data-driven strategies. The other options, while related to various aspects of data collection and analysis, do not specifically focus on the visual evaluation of graphs in the context of behavioral data analysis.