The best way to test a hypothesis is through controlled, systematic, and reproducible experiments. Proper experimental design is critical for obtaining usable, reliable, and applicable data. There are two important components to be considered: variables and controls.
Variables are the conditions and components that are changeable and controllable during an experiment. There are both independent variables and dependent variables.
Independent variables are factors that can be intentionally changed and their impact can be measured on the dependent variable.
Dependent variables are the outcomes or what happens as a result of the independent variable(s).
There are typically many independent and dependent variables to consider when performing an experiment, but it is often best to alter only one independent variable at a time to accurately gauge the effect of that variable on the dependent variable. Multiple independent variables can be changed if you are interested determining a combined effect.
Controls are the components and conditions that are known and kept constant during an experiment. Controls are used for a point of reference and they are often safeguards against internal factors that may influence the outcome of an experiment. Different types of experiments may require different types of controls, depending on the testing procedures. The three main types of controls are positive, negative, and experimental controls.
A positive control is something known to produce a positive result and will often be included (especially for diagnostic tests) to ensure that a negative result is not due to experimental or reaction failure.
A negative control is something known to produce a negative result and will often be included to ensure that a positive result is truly positive and not due to contamination or other interference.
Experimental controls (or “control groups”) are used in controlled experiments to acquire baseline data. This baseline data can be compared to the experimental data to see the relative effect (if any) of the independent variable(s) on the dependent variable. This type of control is a parallel of the experiment, except no changes are made to any of the independent variables. Sometimes an experimental control is also a negative control, depending on the expected outcome and type of experiment. An experimental control can have an outcome similar to the experimental subject if the independent variable does not greatly impact it, whereas with a negative control, no outcome is expected at all.
Determining what types and how many controls to include in an experiment can affect the reliability and accuracy of your data and ultimately your conclusions.
Data Collection and Analysis
Once the experiment is designed, decide what type of data you need to collect and how you will collect it in order to evaluate your hypothesis. Consistency when making measurements and collecting data is important to ensure accuracy, precision, and ultimately repeatability of your experiment. When you perform any experiment, be sure to record all your findings, preferably in ink. Good record keeping, observations, and notes will help you make a more thorough and reliable analysis of your data and will give more credibility to your results.