Testing Hypotheses With Controlled Experiments
Suppose you decide to grow bean sprouts in your kitchen, near the window. You put bean seeds in a pot with soil, set them on the windowsill, and wait for them to sprout. However, after several weeks, you have no sprouts. Why not? Well, it turns out you forgot to water the seeds. So, you hypothesize that they didn’t sprout due to lack of water.
To test your hypothesis, you do a controlled experiment. In this experiment, you set up two identical pots. Both contain ten bean seeds planted in the same type of soil, and both are placed in the same window. In fact, there is only one thing that you do differently to the two pots:
- One pot of seeds gets watered every afternoon.
- The other pot of seeds doesn’t get any water at all.
Let’s see how this simple example illustrates the parts of a controlled experiment (see figure below).
Control and Experimental Groups
There are two groups in the experiment, and they are identical except that one receives a treatment (water) while the other does not. The group that receives the treatment in an experiment (here, the watered pot) is called the experimental group, while the group that does not receive the treatment (here, the dry pot) is called the control group. The control group provides a baseline that lets us see if the treatment has an effect.
Independent and Dependent Variables
In contrast, the dependent variable in an experiment is the response that’s measured to see if the treatment had an effect. In this case, the fraction of bean seeds that sprouted is the dependent variable. The dependent variable (fraction of seeds sprouting) depends on the independent variable (the amount of water), and not vice versa.
Experimental data (singular: datum) are observations made during the experiment. In this case, the data we collected were the number of bean sprouts in each pot after a week.
Variability and Repetition
Out of the ten watered bean seeds, only nine came up. What happened to the tenth seed? That seed may have been dead, unhealthy, or just slow to sprout. Especially in biology (which studies complex, living things), there is often variation in the material used for an experiment – here, the bean seeds – that the experimenter cannot see.
Because of this potential for variation, biology experiments need to have a large sample size and, ideally, be repeated several times. Sample size refers to the number of individual items tested in an experiment – in this case, 10 bean seeds per group. Having more samples and repeating the experiment more times makes it less likely that we will reach a wrong conclusion because of random variation.
Biologists and other scientists also use statistical tests to help them distinguish real differences from differences due to random variation (e.g., when comparing experimental and control groups).