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Understanding science: a basic vocabulary

27 May 2014, 19:10
By necessity, the language of science is more precise than the general, everyday language we use on a daily basis. The scientific meaning of a word may differ or be more precise than the dictionary meaning of a word. This is often a source of great confusion for people who listen to or interact with scientists.

It is also a source of frustration for scientists, who are often misunderstood through the use of words they take for granted, but which to the general public may have a completely different meaning.


I’m going to try to explain some of these words in both their general and scientific meanings to clear up some of the confusion.

Observation:

General meaning – Something that is witnessed directly with your own eyes.

Scientific meaning – Something that is witnessed either directly with the observer’s own eyes or witnessed through the use of a properly calibrated instrument.

There are things that we simply cannot see. Things like black holes, which by definition we cannot see, or neutrinos. We can, however, see their effects, either directly, as in the case of black holes, or indirectly through the use of instruments, as is the case with neutrinos – or electricity for that matter.

In both cases, it is the act of observation that is central to science. It must be seen either directly or indirectly, but it must be observable in order to be considered falsifiable.

This does not imply that you need to see an event occurring directly. If that was the case, there would be no point in recording history. We know of past events not just because they are recorded. We know of past events because of the traces left behind. Until the discovery of ancient Troy by Heinrich Schliemann, Troy’s existence was considered a myth. But because of the discovery of the city, we know that Troy existed, even though we never saw ancient Troy.

Likewise, we know what happened in our solar system, or shortly after the beginning of time, through the evidence left behind which we can view today, even though the event actually occurred hundreds, thousands, millions or billions of years ago.

Falsifiable:

There is a difference between falsified and falsifiable.

General meaning – Falsified in general means that something have been shown to be false. Scientists also use that word in that context.

Scientific meaning – Falsifiable on the other hand, means testable. In order for something to be considered falsifiable, you must be able to perform a test or make an observation that might provide evidence as to its veracity. In general, you must be able to provide evidence to prove an idea false in order for something to be considered falsifiable.

Why is this important? Because it requires the collection of data, or evidence. The data you collect to support a hypothesis can easily prove the hypothesis wrong. If it doesn’t then the hypothesis stands. But because it might be proven wrong at any time through the collection of new evidence, it can be considered falsifiable.

This is one of the bedrock foundations of the scientific method, and is also why scientists will never say anything is 100% certain. New evidence can always present itself which might require a rethink. Which neatly brings us to the next word: uncertainty.

Uncertainty:

General meaning: The dictionary defines uncertainty as the state of being uncertain, or of not knowing for sure.

Scientific meaning: Scientists use the statistical meaning, that being: the range of values within which the true value is likely to fall.

A good example would be the precision of instruments. Think of your kitchen scale and its accuracy. On the old analogue scales, you often couldn’t tell the true mass of your ingredients, but you could get a decent estimate. When measuring 100g of sugar, the reading could be anything between 95g and 105g, and you couldn’t really be sure which it is, but it’s close enough for the purpose.

For those of you who are lucky enough to work in labs, you’ll know that mass can be measured much more accurately with a balance, where your precision increases into three decimal points, say 100.543g.

Uncertainty comes into play here. When you measure on a scale with an accuracy to the last gram, you can’t be sure of what the decimal point values are. It might be 100.567g, but your instrument can only read to 100g accuracy. This is what scientists mean when they speak of uncertainty, and also our next word, error.

Error:

General meaning – A mistake.

Scientific meaning – The statistical difference between the measured value and the true value.

As I explained under uncertainty, there are inherent limits to scientific instruments. The balance we use in the lab can only measure the decimal points up to a certain point, and after that, we’re uncertain as to what the value would be. However, we can know to what degree we are uncertain. We call this error.

Those of you who have worked in a lab will know that most scientific instruments give an indication of the inherent error they allow for. A pipette may show a volume of 1ml +/- 0.1ml. Or 1ml +/- 0.01ml. That 0.1ml is the error of the instrument, or the value of the potential difference between the real and measured value.

This also plays a role in statistics when we calculate the confidence limits of numerical data: the higher the error, the less your confidence limit will be. For most statistical purposes, a 95% confidence limit is considered acceptable. Others work on a 99% confidence limit. It depends on the level of precision required.

Note that a 100% confidence limit can never be reached, because we simply cannot measure for an infinite number of decimal spaces. This isn’t meant to be an exhaustive discussion on statistics, however, so if you’re interested in that, feel free to read up more.

Prediction:

General meaning – A statement about a future outcome. In other words, something along the lines of what Nostradamus would say.

Scientific meaning – Expected outcome if a hypothesis or idea is correct.

In scientific terms, prediction may have absolutely nothing to do with the future. It’s simply a component of scientific testing, of falsifiability. Let’s take an example from Newton’s law. If I throw a rock with a certain force, at a certain angle, then according to Newton’s law, the rock will fall a certain distance away from me. That is a scientific prediction. If Newton’s law holds true, then that rock will fall at a specific place in relation to where I’m standing and the direction in which I threw it.

If I board a plane in Cape Town, and I fly in a straight line to Johannesburg at a certain speed, I will arrive at a certain time. That is a scientific prediction. If evolution holds true, then I should see a progression in the fossil record from single celled to multicelled organisms. That is also a scientific prediction, even though that progression happened millions or even billions of years in the past.

In scientific terms, prediction has nothing to do with the past or the future, but with the expected result if a theory holds true.

Belief/believe:

General meaning – Belief is a tricky one to define, even in general terms. It could mean you trust something to be accurate, or you support a cause. It implies having faith in something regardless of the availability of evidence.

Scientific meaning – Accepts. That’s the long and the short of it. When a scientist says that she believes in something, she means that she accepts it based on the available evidence.

Scientific belief has nothing to do with dogma, conviction or faith. It is merely the acceptance of something because there is sufficient data to support it. Just as theories may change, so do scientific beliefs. It’s based on the available evidence. Which brings us to the next one: theory.

Theory:

General meaning – a hunch.

Scientific meaning – A concise explanation for a broad range of observed phenomena.

A scientific theory is a unifying framework within which a large number of observed phenomena may be explained. Let’s look at the big one, why not: the theory of evolution through natural selection.

Let’s first look at some of the phenomena that fits into the general theory. First, you have genetic heritability as first described through experiment by Mendel in the 1800s. You have broad similarities between different groups of animals as described by Linnaeus in the 1700s. You have a fossil record as first described as such in the 1800s.

These are all different phenomena described by different scientists, which are all tied together and explained through Darwin’s theory of evolution through natural selection. It takes all that observed phenomena, provides a unified explanation, and provides a mechanism through which the phenomena can be tied together.

This is, in general terms, what a scientific theory is. The same applies to Newton’s theory of gravity, or Einstein’s theory of general relativity. All of those took an observation, and derived from that a set of “rules” which are universally applicable, and a mechanism through which the observed phenomena are explained.

In Newton’s case, the legend goes that the apple fell on his head. I wonder why the apple fell on my head. What causes the apple to fall. Could other things also fall like the apple falls? Through notation and observation, Newton calculated the laws of gravity and rotation, giving us Newtonian physics.

However, the basic framework for it all is still called Newton’s theory. Not because it’s a hunch or anything. It’s simply the proper terminology to fit in with the concept of falsifiability.

Hypothesis:

General meaning – A guess.

Scientific meaning – A proposed explanation for a specific phenomenon.

Where theories are explanations covering a number of phenomena, a hypothesis deals with only one. Our scientist who wanted to know why the water was hot dealt with a hypothesis. He wanted to explain only one thing. Newton on the other hand ended up explaining any number of things, from orbital mechanics to vector physics.

That is the difference between a hypothesis and a theory. Both can be tested, and have the scientific method applied to it. Which you use is largely a matter of scale.

I hope this was of some help. I realise I didn’t discuss each in depth. That was not my intent. Hopefully you now have a better idea of some of the scientific terms and how they can be misinterpreted and misused.

(I was going to post this one a bit later on, but after reading some of the comments yesterday, I decided to move it forward a bit. And speaking of comments: thank you for the positive feedback! I appreciate it. I do read the comments, but unfortunately, I can't log in from work, and by the time I get home, most of the discussions are over, so it seems pointless to post after the fact. :P 

The next article will deal with testing hypotheses.)

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