The scientific method is a systematic and logical approach to discovering how things in the universe work. It is the backbone of modern science and has led to many of the technological advancements we enjoy today
Scientists value verifiable and reproducible results more than anything else as the basis for knowledge. The scientific method (when done right) is a great way of separating subjective opinions and biases from facts. However, the scientific method does not prove the ‘truth’ about something or a phenomenon — it is simply a method for approximating the truth and the intricacies of the universe. Despite this shortcoming, it is best tool we have for this purpose at the moment.
What is the scientific method?
Knowing stuff is easy. The hook, as we’ve found through our blunderings in the world, is that only part of the things we know are true — and chafing the wheat, so to speak, can prove problematic. It mostly comes down to the fact that each of us harbors innate biases about the way things are in the world, be them a product of our biology, our upbringing, or simply of our limited perception of the universe. Thankfully, we’ve also come up with a set of principles to help overcome these biases and learn the truth about the world, one small step at a time. Because our fancy mental toolkits need a cool name, we’ve labeled that set of principles ‘the scientific method.’
But it’s not only for scientists. The method is a more organized version of the same deduction processes we use in everyday problem-solving and can help you in your day-to-day life. It’s great for getting to the root of things and eliminating add-on (but irrelevant) factors through repeated tests and tweaks to the object of your interest. That being said, let’s look at how it’s done.
Steps to the scientific method
The scientific method is not a set of fixed steps that must be followed in a rigid order, but it is a flexible framework that allows scientists to adapt their methods to the question they are trying to answer. A commonly used step-by-step framework for the scientific method might look something like this:
- Observe
- Hypothesize
- Predict according to the hypothesis.
- Experiment.
- Observe and analyze the results
- Communicate your findings
Observation is the basis of science as we understand it today and forms the first step in the scientific method. It can be something really simple and obvious, like “cats like to eat meat”, or something not readily apparent — “there is an infinite number of decimals in π,” for example.
For example, Galileo Galilei observed that two balls of different weights dropped from the Leaning Tower of Pisa fell at the same rate, regardless of their weight. This observation led him to question the prevailing belief that heavier objects fall faster than lighter ones. Aristotle had previously claimed that force causes speed, but this was disproved by Galileo who found that force causes acceleration. Galileo’s observation was the starting point for his investigation into the laws of motion, which laid the foundation for modern physics.
Observations naturally lead to a question — “well, why do cats eat meat?” — and our attempt at answering this will first require looking at available data. This can come from your own previous observations, other scientists’ papers, and so on. So let’s say that while reading up on your cat’s culinary preferences, all you found was that “cats don’t eat spinach.” Previous experience with your pet also tells you that “cats like to drink milk.” Beyond that, not a word.
That didn’t answer your question, so you’re now in uncharted waters and an idea is forming in your mind — “cats only eat red and white food, since meat is red and milk is white.” That’s your hypothesis. It’s important to keep this hypothesis falsifiable, meaning there is a possible negative answer, so you can test it and see how it fares against reality.
You start doing that with a prediction. It sounds fancy, but it’s pretty simple and you probably do it all the time, anyway: prediction basically means drawing a logical conclusion as to how the world would behave if your hypothesis was true or if it wasn’t.
We predict that our cat will eat fresh tomatoes because they’re red, and some flour, because it’s white, but it will never eat cat food since it’s… brownish, nor butter, which is yellow. That prediction is easily verifiable with an experiment. Offer your cat the four foods and lo and behold, the tomatoes and flour are left untouched while the cat food is all gone and the butter seems nibbled on — the experiment’s results conflict with your hypothesis. Based on the new data, you can alter the hypothesis, create new predictions based on that, and re-take the test. Or you may have to reject it altogether.
Image credits Thebiologyprimer / Wikimedia.
Experiments need to contain a dependent variable — which stays constant — and an independent variable (which changes), so you can compare and isolate their effects. Similarly, some experiments require a control and an experimental group for comparison in order to tease out the effect of a variable, which may be a new drug or therapy. A control group comprises participants who do not receive the experimental treatment. Use both inductive and deductive reasoning to work on your hypothesis. Finally, when testing it, go for the falsifying experiment if you can. If your hypothesis holds true in a riskier experiment, it will do much more to confirm it that a slew of low-risk ones.
Although the scientific method aims at taking chance and bias out of the pursuit of knowledge, these can never be entirely eliminated — maybe one cat out there actually likes flour and tomatoes. Keep in mind that a single positive result doesn’t prove a hypothesis right, and one negative result doesn’t make it wrong. It’s all a matter of confidence and there are several degrees of confidence that we can infer using statistical methods.
The scientific method is a self-correcting process. It allows for new information and new evidence to be considered, and it can lead to the rejection of a previously accepted hypothesis.
Once the data has been collected, scientists analyze and interpret it. They use statistical methods to determine whether the data supports or refutes their hypothesis. The results of the analysis are used to draw conclusions and make inferences about the natural world.
For example, Galileo analyzed the data from his experiments and found that the time it took for spherical objects with the same volume but of different weights to fall was the same. He concluded that the rate at which objects fall towards the ground is independent of their mass while at the same time disproving Aristotle’s theory of gravity (which states that objects fall at a speed proportional to their mass). Four centuries later, Astronaut David Scott performed a version of the experiment on the Moon during the Apollo 15 mission in 1971, dropping a feather and a hammer from his hands. Because of the negligible lunar atmosphere, there was no drag on the feather, which reached the lunar surface at the same time as the hammer.
Galileo’s landmark findings represent a fantastic example of how science is self-correcting and builds upon itself with new discoveries. It also shows how our scientific theories are not really static but are subject to change in the face of more convincing evidence.
The final step in the scientific method is communication. Scientists share their findings with other scientists through publications and presentations. This allows other scientists to replicate the experiments, review the data, and provide feedback. The scientific community then uses this feedback to evaluate the findings and determine their validity.
For example, Galileo published his findings in 1638 in a book called “Two New Sciences.” This book was widely read and discussed by other scientists, and it played a major role in the development of modern physics.
What is a hypothesis?
After making observations and identifying a question or problem, scientists formulate a hypothesis. Hypotheses are statements that are limited in scope and regard specific situations. A hypothesis is a proposed explanation for an observation or phenomenon. It is a prediction that can be tested through experimentation.
For example, when Galileo observed that identical objects but different in mass dropped from the Leaning Tower of Pisa fell at the same rate, he formulated the hypothesis that all objects fall at the same rate, regardless of their weight. Galileo’s hypothesis was a bold prediction that challenged the prevailing belief of his time.
Or take a more modern and relatable predicament. If your phone won’t power on, you might say “the battery is dead,” and that’s your hypothesis. Then you plug it in the charger and try again, thereby experimentally testing the hypothesis. If it still doesn’t work you’ll rework your hypothesis in order to find the root cause of the malfunction — perhaps “the screen is broken, and it needs to be repaired.”
What is a scientific model?
A scientific model is a simplified representation of a complex system or phenomenon. It is used to explain and predict the behavior of the system or phenomenon being modeled.
A good example is the Bohr atomic model, which shows electrons in an atom are arranged in specific energy levels, or shells, around the nucleus. For illustrative purposes, it is a fantastic learning tool that accurately represents the energies of the quantum states of the electrons in an atom. It is, however, incomplete. The Electron Cloud model is a lot more accurate to real life, depicting the position of electrons as a cloud of probability rather than as spheres orbiting a nucleus like planets around the sun.
One important thing to keep in mind is that scientific models are not always perfect, they are approximations of the real system and can be limited by the current understanding and data available. Therefore, scientific models are always subject to refinement and revision as new data and insights become available.
What is a theory?
Theories are frameworks of hypotheses that have been repeatedly confirmed through experiments. They’re not really proven correct per se, but they’ve never actually been proven wrong so they can’t be discarded. New discoveries usually fit into existing theories, and it’s only after one of these discoveries can’t be reconciled with it that scientists try to modify the theory. Sometimes theories become laws.
It is different from the way the word “theory” is commonly used in everyday language, where it often refers to a hunch or a speculation. In science, a theory must be based on empirical evidence and has been repeatedly tested and confirmed through scientific experimentation and observation. Theories that have been repeatedly tested and confirmed over time are considered to be well-established and unlikely to change. Examples of scientific theories include the theory of evolution and the theory of gravity.
What is a ‘law’ of science?
Laws are generally considered to be fundamental and universally relevant in their field, though some laws have been modified over time as our understanding of the world became more refined.
Unlike a scientific theory, which is a well-substantiated explanation of some aspect of the natural world, a scientific law is a statement that describes what happens in the natural world. It is a statement that is always true under certain conditions and is independent of time and place. Examples of scientific laws include the law of gravity, the laws of thermodynamics, and the laws of motion.
Common errors and limitations
One of the most fundamental errors is to mistake the hypothesis for the full explanation of a phenomenon without performing any test. Even if it seems logical or of common sense that the hypothesis is true — until tested it is only a hypothesis. Thinkers as far back as ancient Greece have pointed out this fallacy.
Another wrench commonly thrown in the scientific method is to ignore data that doesn’t support the result you’re after. Ideally, the experimenter should be unbiased. However, our brains are really good at justifying “something wrong” in certain data under strong personal beliefs or due to perceived pressure to get a specific result. All data is equally important, and there is no such thing as a bad result in science.
A failure to account for errors may reveal discoveries that aren’t there or may hide legitimate findings.
And finally, because the scientific method relies in great part on repetition and reiteration, some phenomena which can’t be repeated and/or measured again and again don’t lend very well to its use. If you’re trying to woo the focus of your affection, for example, and it goes poorly, you can’t restart in front of the same person and try again, over and over, until you find the best approach. The same person will still be influenced by what you said before. A new person will react differently.
That, in a nutshell, is the scientific theory. The scientific method is a way of constantly checking the validity of our reasoning while we go along, of knowing how we know. It is a mental tool freely available to all, not just professional scientists who do this for a living.
Observe, deduce, and test. Always take evidence over preference, and try to look at as few variables at a time as possible in your experiments. Remember that your hypotheses may turn out to be false, and that your assumptions are working against you — if you want to find the scientific truth, always keep an eye out for something that might reduce the accuracy of your results, especially yourself.
