Science is messy. If you remember the posters from middle school with the neat, five-step purple arrows—observation, hypothesis, experiment, result, conclusion—honestly, they lied to you. It's never that clean. In reality, what does scientific method mean in science is less about a rigid checklist and more about a mindset of organized skepticism. It is a way to stop ourselves from lying to ourselves. Humans are naturally great at finding patterns, even when they aren't there. We see faces in clouds and "winning streaks" in gambling. The scientific method is the harness we put on our brains to keep us from drifting into pure fantasy.
Think about the last time your Wi-Fi cut out. You didn't just sit there. You probably checked the router lights. Then you checked your phone. Maybe you toggled the airplane mode. That’s science. You made an observation (no internet), formed a tiny hypothesis (the router is acting up), and ran an experiment (the power cycle). You’re already doing it.
Why "What Does Scientific Method Mean in Science" Isn't Just for Scientists
At its heart, the scientific method is the process of building a model of the world that actually works. We used to think diseases were caused by "miasma" or bad air. It sounded logical at the time because swamps smelled bad and people got sick near them. But when people like John Snow—not the Game of Thrones guy, but the 19th-century physician—started mapping cholera outbreaks in London, he realized the "bad air" theory didn't hold water. Literally. By tracking the Broad Street pump, he used data to prove the water was the culprit.
This is the core of scientific inquiry. It’s a loop.
You start with an Observation. This is just looking at the world and saying, "Huh, that's weird." Why does the moon change shape? Why do some plants grow faster in the shade? From there, you move to the Hypothesis. This is the part people get wrong most often. A hypothesis isn't just a "guess." It has to be a testable, falsifiable statement. If you say, "The Wi-Fi is down because invisible space ghosts are blocking the signal," that isn't a scientific hypothesis because there is no way to prove it wrong. If you can't test it, it's not science; it's just a story.
The Power of Falsification
Sir Karl Popper, one of the most influential philosophers of science in the 20th century, argued that the defining feature of science is falsifiability.
Most of us want to prove we are right. Scientists, at least the good ones, are trying to prove themselves wrong. If I think all swans are white, I shouldn't go looking for more white swans. I should be hunting for a single black swan. Once I find it, my theory is dead, and I have to build a better one. This is why you’ll rarely hear a cautious scientist say they have "proven" something. They say the evidence "suggests" or "supports" a theory. They leave the door open for new data to kick the old ideas over.
The Architecture of an Experiment
The Experiment is the meat of the process. This is where you isolate variables.
Imagine you’re testing a new fertilizer. You can't just put it on one plant and see if it grows. What if that plant got more sunlight? What if it’s just a "stronger" seed? You need a Control Group. This is the baseline. One group of plants gets the fancy new chemicals (the experimental group), and the other gets plain old water (the control group). Everything else—light, soil, temperature—must be identical.
If the fertilized plants grow six inches taller, you might be onto something. But you're still not done. You need Replication.
One of the biggest crises in modern science right now, especially in psychology and medicine, is the "Replication Crisis." A 2016 survey by Nature found that about 70% of researchers had tried and failed to reproduce another scientist's experiments. If I do an experiment in my lab in New York and get a result, but you do the exact same thing in London and get something different, my result was probably a fluke. It wasn't "real" in the scientific sense.
📖 Related: Crazy Fucking Robot Body: Why We Are Obsessed with the Future of Synthetic Anatomy
Data and the "Aha!" Moment
Data isn't just numbers. It’s the story the world is telling us.
When researchers at CERN were looking for the Higgs Boson, they weren't looking for a little ball of matter. They were looking for specific spikes in data among billions of particle collisions. It took years. It took the Large Hadron Collider—a 27-kilometer ring of superconducting magnets.
But sometimes, the "aha!" moment is actually a "that’s funny..." moment. Alexander Fleming didn't set out to invent penicillin. He left a petri dish out, and it got moldy. He noticed the bacteria wouldn't grow near the mold. He could have just thrown it away. Instead, he asked why. That’s the scientific method in its most raw, human form.
Common Misconceptions About Scientific Theories
People often say, "Evolution is just a theory," or "Big Bang is just a theory."
In common speech, "theory" means a hunch. In science, a Theory is the highest level of certainty you can reach. It’s an explanation that has been tested over and over and has never been proven wrong. Gravity is a theory. Germs causing disease is a theory. Tectonic plates moving the Earth's crust is a theory.
📖 Related: 0.0001 BTC in USD: Why This Tiny Fraction Actually Matters for Your Wallet
- Laws describe what happens (like the Law of Gravity telling us how fast things fall).
- Theories explain why it happens (like General Relativity explaining that gravity is the warping of spacetime).
Theories don't "graduate" into laws. They are different tools for different jobs.
The Human Element: Bias and Peer Review
Scientists are people. They have egos. They want to be famous. They want to get tenure. This is why Peer Review is so critical to what scientific method mean in science.
Before a study gets published in a major journal like Science or The Lancet, other experts in the field tear it apart. They look for math errors. They look for biased samples. They ask if the conclusion actually follows the data. It’s a brutal, slow, and frustrating process, but it’s the best filter we have for nonsense.
Even then, it’s not perfect. Bias can creep in. Sometimes it’s "p-hacking," where researchers manipulate data just enough to make it look statistically significant. Sometimes it’s funding bias, where a study funded by a sugar company miraculously finds that sugar isn't that bad for you. This is why transparency and open data are the next frontiers of the method.
Real-World Application: The Vaccine Race
We saw the scientific method happen in real-time during the COVID-19 pandemic.
- Observation: People are getting sick with a new respiratory virus.
- Hypothesis: An mRNA sequence can teach the body to recognize the "spike protein" of the virus.
- Experiment: Phase I, II, and III clinical trials involving tens of thousands of people.
- Data Analysis: Comparing infection rates in the vaccinated group vs. the placebo group.
- Peer Review: Independent boards and the FDA reviewing every scrap of data.
It was fast, but it followed the rules. It didn't skip the steps; it just did them in parallel because the stakes were so high.
👉 See also: What is a Mobile Phone Jammer and Why Are They Actually Illegal?
How to Think Like a Scientist Every Day
You don't need a lab coat. You just need to be comfortable being wrong.
When you hear a crazy claim on social media, ask: What is the evidence? Is there a control group? Is the source biased? Could there be another explanation? Most people look for information that confirms what they already believe. This is called Confirmation Bias. To use the scientific method in your life, you have to actively look for information that proves you wrong.
It’s uncomfortable. It’s annoying. But it’s the only way to actually get closer to the truth.
Practical Steps for Evaluating Information
Next time you encounter a "scientific" claim, run it through this mental filter:
- Check the Sample Size: Did they test this on five people or five thousand? Small samples lead to flukes.
- Look for the "Why": Does the explanation make sense, or is it just a correlation? (Ice cream sales and shark attacks both go up in the summer, but ice cream doesn't cause shark attacks).
- Verify the Source: Is this a peer-reviewed journal or a blog post selling supplements?
- Demand Replication: Has anyone else found the same result?
Science isn't a collection of facts. It's not a textbook full of answers. It is a process of constant correction. It's a way of saying, "I think this is true, but I'm willing to change my mind if the data says otherwise." That's the most powerful way to think that humans have ever invented.
Start by questioning your own assumptions. Pick one thing you're "sure" of today and look for the best argument against it. See where the evidence actually leads. You might be surprised.