The number of independent variables an investigation should have depends on the research design and objectives. Typically, an experiment should have only one independent variable to ensure that the effect on the dependent variable can be clearly attributed to that one factor. This is important to maintain internal validity and avoid confusion about which variable caused any observed changes. However, it is also common in more complex experiments to include multiple independent variables. This allows researchers to examine the individual effects of each variable as well as interactions between them. In factorial designs, there can be two or more independent variables, often up to three to keep the number of experimental conditions manageable and feasible. More than three independent variables become difficult to handle due to the exponential increase in conditions and required sample size. In summary:

• For simple experiments or when clarity is paramount, use 1 independent variable.
• For more complex investigations addressing multiple factors or interactions, 2 or 3 independent variables can be used.
• Designs with more than 3 independent variables are uncommon due to complexity and resource demands.

This flexibility depends on study goals, resources, and design constraints.