In an experiment, you can technically have multiple independent variables, but it’s important to limit them to avoid complications in your results. Generally, experiments are designed with one independent variable being manipulated at a time to clearly observe its effect on the dependent variable. However, there are situations where researchers may include two or more independent variables, especially in factorial designs, where the interaction between variables is also being studied.
The main reason to restrict the number of independent variables is to maintain clarity. Each independent variable can introduce its own complexity and potential confounding factors, making it harder to determine the effect each variable has on the dependent variable. If you decide to include more than one independent variable, make sure to have a solid experimental design that can adequately test and analyze the interactions.