True or False: Increased variability makes it difficult to predict future patterns, which is necessary for experimental control.

Increased variability in data indicates that there are greater fluctuations or inconsistencies in the observations or measurements being taken. When data is highly variable, it becomes challenging to identify consistent patterns or trends. This unpredictability directly impacts the ability to establish experimental control, which relies on the ability to anticipate outcomes based on previous observations.

For experimental control to be effective, it is important to have a reliable and repeatable relationship between the independent and dependent variables. High variability can obscure these relationships, making it difficult to draw conclusions or make predictions about future behavior based on prior data. In essence, predictability is crucial for establishing control within experiments, and increased variability undermines that predictability.

In contrast, lower variability typically allows for more accurate predictions and a stronger basis for experimental control, fostering a more reliable understanding of the relationship being studied. Thus, the statement that increased variability makes it difficult to predict future patterns, which is necessary for experimental control, is True.