Final answer:
It is false that every experiment should only have one independent variable, as some experiments manipulate multiple variables, but it complicates attributing effects. Control groups are key to isolate the effects of the independent variable. The scientific method values all data and embraces multiple investigation methods.
Step-by-step explanation:
According to the principles of scientific experimentation, it is false that every experiment should have only one independent variable. While it is ideal to have a single independent variable to draw a clear cause and effect relationship, there can be situations where multiple independent variables are manipulated. However, when multiple independent variables are present, it can be challenging to attribute the changes in the dependent variable to a specific independent variable. This might lead to confounding results.
The control group should be identical to the experimental or test group in every aspect except for the independent variable being tested. This ensures that any observed changes are due to the independent variable and not other extraneous factors. The control serves as a benchmark to measure the effects of the independent variable.
Larger sample sizes are usually advantageous over smaller ones as they help in reducing random error and increasing the reliability of the results. Experiments can be conducted on humans, provided they meet ethical standards. Notably, data that does not support a hypothesis is still useful, as it can guide future research directions and hypothesis refinement. Experimentation is a chief method but not the only type of scientific investigation.