Experimental Design

No matter how much time, effort, and resources you put in, a poorly designed experiment will always yield unreliable and invalid results. Arguably, the most important part of conducting an experiment is the design and planning stage; when this is done correctly, you can be more sure that what you are testing is going to give you results that you can trust. 

Experimental design is the cornerstone of rigorous scientific inquiry, providing a structured and objective framework for systematically investigating phenomena, testing hypotheses, and discovering cause-and-effect relationships. 

The main objective of experimental design is to establish the effect that an independent variable has on a dependent variable.¹ What does this mean, exactly? 

Say, for instance, you're trying to understand how the amount of sleep someone gets at night affects their reaction times. In this scenario, the independent variable is the number of hours of sleep, while the dependent variable is reaction time—as it depends on changes in sleep. In the experiment, the independent variable (sleep) is controlled and adjusted to observe its effect on the dependent variable (reaction time). When experimental design is applied correctly, the researcher can be more confident about the causal relationship between sleep duration and reaction time.

As a general rule of thumb, setting up an experimental design includes the following four stages: 

1. Hypothesis: Establish a “testable idea” that you can determine is either true or false using an experiment. 
2. Treatment levels and variables: Define the independent variable to be manipulated, the dependent variable to be measured, and any extraneous conditions (also called nuisance variables) that need to be controlled. 
3. Sampling: Specify the number of experimental units (a fancy way of saying participants) that are needed, including the population from which they will be sampled. To be able to establish causality between an independent variable and a dependent variable, the sample size needs to be large enough to provide statistical significance. 
4. Randomization: Decide how the experimental units will be randomly assigned to the different treatment groups—which usually receive varying “levels” of the independent variable, or perhaps none at all (this is called a control group).

So, what distinguishes experiments from other forms of research? Of the four stages described above, the manipulation of independent variables and the random assignment of participants to different treatment groups are what truly set an experimental design apart from other approaches.² Meanwhile, creating a hypothesis and choosing which population to study are common processes across a range of research methodologies. 

There are several different types of experimental design, depending on the circumstances and the phenomena being explored. To better understand each one, let’s refer back to our above example of testing the impact that sleep has on reaction time.

• An independent measures design (also known as between-groups) randomly assigns participants into several groups each receiving a different condition. For example, one group might get 4 hours of sleep per night, another group might get 6 hours of sleep per night, and a third group might get 8 hours of sleep per night. The researchers would then measure each group’s reaction time to assess how different amounts of sleep impact response speed.
• Meanwhile, in a repeated measures design, the same participants would experience all of the conditions. First, they might get 4 hours of sleep, then 6 hours, and finally 8 hours (in different phases of the experiment). Their reaction time would be measured after each condition to see how their performance varies depending on the amount of sleep they received.
• Finally, a matched pairs design creates pairs of participants according to key variables such as their age, gender, or socioeconomic status. For our example study, one member of each pair would get 6 hours of sleep, while the other would get 8 hours. Their reaction times would then be compared to see how sleep duration affects response speed.

Each experimental design comes with its own unique set of pros and cons. It’s up to the researcher to decide which one is best depending on the objectives of the study and the number of factors that need to be investigated.