You hypothesized that pressing the button marked with the up arrow would not only bring an elevator to you, but that it would be an elevator heading in the up direction. As this guide explains, the deliberate process of testing hypotheses and reaching conclusions is an extension of commonplace testing of cause and effect relationships.
Discovering causal relationships is the key to experimental research.
In the Mega Gro experiment discussed below, the plants might be matched according to characteristics such as age, weight and whether they are blooming.
This involves distributing these plants so that each plant in one group exactly matches characteristics of plants in the other groups.
In addition, you could observe that turning the knob clockwise alone, and nothing else, caused the sound level to increase.
You could further conclude that a causal relationship exists between turning the knob clockwise and an increase in volume; not simply because one caused the other, but because you are certain that nothing else caused the effect.
An experimenter who wants to show that adding a certain fertilizer will help a plant grow better must ensure that it is the fertilizer, and nothing else, affecting the growth patterns of the plant.
To do this, as many of these variables as possible must be controlled.
In this example, even though the designers of the experiment have tried to remove all extraneous variables, results may appear merely coincidental.
Since the goal of the experiment is to prove a causal relationship in which a single variable is responsible for the effect produced, the experiment would produce stronger proof if the results were replicated in larger treatment and control groups.