How are multiple-step experiments characterized?

Multiple-step experiments are characterized by being structured as a sequence of steps, where each step may represent a different action or decision that leads to a final outcome. This framework allows researchers or analysts to break down complex processes into manageable components, making it easier to analyze and interpret the results at each stage.

In such experiments, each "step" represents a specific trial or decision point, and the outcome of one step can often impact subsequent steps. By organizing the experiment in this way, it enables clearer understanding and visualization of the process involved, and it can be more effectively managed statistically, especially in areas such as probability and decision making.

This methodology is essential for understanding how the effect of one decision might influence subsequent decisions and outcomes, contributing to the overall analysis of the experiment.