matt zinselmeier

Why Science?

Why Science?

1.3.16 | Matt Zinselmeier

Why Science? If you open up Webster’s Dictionary, you’ll find science defined loosely as “systematic knowledge of the physical world gained through observation and experimentation.” In other words, science is a process; the process of gathering & understanding information that leads to logical conclusion. While it’s obviously safe to assume scientists subscribe to this methodology, I would argue almost every individual on the planet employs some sort of scientific logic each day. Science is why we are alive today. It has allowed the human race to progress technologically, and as a result societally. And it’s not just a few individuals responsible for this progress; the human race has relatively embraced the ideas of scientific logic to benefit the living condition.

Each morning you make a conscious decision as to what clothes you’re going to put on. On most days, this decision isn’t random. Rather, choosing your outfit is a logical deduction stemming from tidbits of pertinent information around you, such as the temperature outside or particular events you have planned for that day. Elementary it may seem, these core principles leading to your clothing decision are conserved and necessary for scientific thinking.

The modern scientific method, devised by the English mathematician and philosopher Roger Bacon (1214-1294), is the general framework of logic employed by scientists across all disciplines to draw seemingly infallible conclusions. While it may not be the best, let’s continue using our clothing decision example to work through the five crucial steps of the scientific method:



(1) Ask a question about some sort of natural phenomenon
• What clothes should I wear today to be comfortable and look nice for others?

(2) Formulate a hypothesis that explains why your phenomenon of interest is occurring
• I should wear jeans and a t-shirt, because they will maximize comfort while I’m sitting in class and show off my voluptuous figure to peers.

(3) Given your hypothesis, make one or several predictions that can specifically verify your hypothesis is necessarily true
• Prediction 1 - During class today, I expect that I will not be restless in my seat.
• Prediction 2 – While walking around campus today, I expect several of my peers to envy my striking looks accentuated by my near-perfect choice of outfit.

(4) Test your predictions by performing experiments. In order to do this, your predictions must be testable!
Testing Prediction 1 – I should start by counting the number of times I readjust my position in my seat during lecture today. We can then compare that number to the number of times I readjusted my seat position on a previous day in that same lecture while wearing a suit. We expect that if your clothes are comfortable, you will squirm fewer times today in comparison to when you wore the suit.
Testing Prediction 2 – I should count the number of times I receive compliments pertaining to how great I look in my jeans and t-shirt. We will compare the number of compliments I receive while wearing jeans and a t-shirt to another day in which I was wearing baggy sweatpants and a hoodie. We expect that if your outfit is indeed showcasing your fantastic looks, you will receive more compliments while wearing jeans and a t-shirt in comparison to the day you wore sweats.

(5) Analyze the data and make logical conclusions
Results for Prediction 1 - The data shows that you readjusted your seat position 5 times during a 50-minute lecture. Approximately 1 readjustment every 10 minutes. Conversely, you readjusted your seat position 10 times while wearing a suit last week during the same 50-minute lecture. Approximately 1 readjustment every 5 minutes. If seat readjustment is an accurate indicator of comfort, it seems your choice of jeans and a t-shirt was more comfortable. Congratulations!

Results for Prediction 2 – You received 20 compliments throughout the day while wearing your jeans and t-shirt. On the day you wore sweatpants, you received 17 compliments pertaining to your looks. Did the jeans and t-shirt work? You turn to a statistical test (you know, the stuff with p-values) and find that the increase of 3 compliments while wearing jeans and a t-shirt vs sweats is not statistically significant.

Conclusion – Your outfit definitely made you more comfortable, nice decision! But, it turns out the outfit didn’t really have a large impact on your appearance to others. This could have occurred for several reasons: the jeans and t-shirt made you look worse, you had a bad hair day today in comparison to when you wore sweats, or maybe you’re just always attractive regardless of what you wear (let’s go ahead and predict it’s the latter). Regardless, our hypothesis needs a little reworking. Changing our hypothesis allows us to conduct more experiments using this same logic chronology to see if our revisions are necessarily true!



Well, we did it. That train of systematic and logical thought is the basis of all science that has been, and probably will ever be, conducted. We asked a question about something, hypothesized why that something may occur, tested our reasoning by making specific predictions, and then analyzed our data to see if the hypothesis was necessarily true. So what is the point of all this? It’s to show that everyone is capable of science. But just because we can all do science doesn’t mean it’s important, right? Well, were it not for science we wouldn’t really know definitively why anything happens. Collecting data pertaining to a hypothesis allows us to accept or reject that hypothesis. In times that we accept the hypothesis, we are essentially stating that our explanation for an event is necessarily true given the data. We can then implement that newfound reasoning into novel technology for the betterment of society.

It’s also important to understand that science doesn’t hold any beliefs. It is the scientists (you in this example) that make a claim based solely on experimental evidence. As enough data accumulates to support a hypothesis, it becomes necessarily accepted in all aspects of life. For example the hypothesis, and now theory, of gravity has an almost irrefutable amount of data supporting its claims. There are no biases or beliefs involved. No matter how plausible a hypothesis may seem in your head, it’s effectively meaningless until data can back its assertions. New data is always accepted, even if it refutes a hypothesis previously supported to be true. This makes science uniquely adept to standing the test of time; regardless of the changing world around us, the scientific method can operate successfully due to its logical nature. Paramount in character is the single incessant and interminable goal of science to accurately ascribe meaning to the natural world.

To at least cite the perpetual stereotype, science isn’t limited to a bunch of introverted recluses sitting in their labs and tinkering. Rather, scientists are a broad range of people unified by the idea that the natural world is mysterious and fascinating. These people then utilize logic and reason to discern an explanation for natural phenomena. Science goes hand-in-hand with curiosity, a hallmark of the human race. In fact, science is the ultimate methodology used to resolve one’s curiosity pertaining to any subject. Ask a question about the material world, no matter how big or how small, and get an answer through experimentation. Moral of the story? We’re all scientists; we just don’t really know it.