Key Points
- "Science" is more than a body of knowledge. It is a way of approaching questions about the natural world.
- Observations (data) about nature are used to develop hypotheses: questions you can test
- Science progresses by the subjecting of hypotheses to tests (experiments) to see if you can reject them; those you cannot reject are provisionally accepted until new information is available.
- ;Scientific studies are presented as papers: publications where scientists state their observations, methods, analytical results, and conclusions. Other researchers can build upon this information; sometimes supporting it, sometimes rejecting it.
What is Science?
Science is not simply "a body of knowledge". Rather, it is the systematic acquisition and application of knowledge about the structure and behavior of the physical universe gained via empirical evidence through observation, measurement, and experimentation. It can be described as a type of inquiry into nature characterized by the availability of empirically testable hypotheses.
Science starts from several important observations about the world around us:
- Humans are limited by our senses: we cannot have total knowledge of the Universe or any part of it
- The world is sensible: it operates under patterns of operation which we can discover, at least partially
- Although we might never totally understand a given phenomenon, we can approximate or model how it works. Using various types of observations, estimates, and so forth, we can make successive approximations which get progressively "better" (that is, closer to the actual answer)
Science is thus a self-correcting mechanism: it contains within its operation the means to get rid of old, less-accurate models and replace them with more accurate ones.
Argument: a connected series of statements intended to establish a proposition, consisting of one or more premises which support the conclusion. (In the case of Science, the premises should be a series of hypotheses tested against observations.) Many, many fields of intellectual endeavor (politics, philosophy, marketing, etc.) relay on arguments. However, Science is distinguished (in a subset of fields: we can add some others like history, economics, etc. in here) by relying on not merely argument but independent evidence: in other words, it is empirical.
There is much talk about the "Scientific Method", often characterized as a hierarchy of observations --> hypotheses --> theories --> laws. This is in some ways an oversimplification, and in others misses the point. These are more the products of Science, not their method. Perhaps a better descriptor of the "Scientific Method" is simply: Physical Evidence and Reasoned Logic (PEARL).
That physical evidence goes by several names: observations, data, measurements, all meaning the same thing: qualitative or (more commonly) quantitative attribute of a phenomenon. In principle, different observes should be able to make the same measurements/descriptions and find the same value.
Of course, we face the issue of uncertainty: there are limitations of observations (for example, the accuracy and resolution of instruments) so we will not always find the same exact value. Additionally, there are probabilistic aspects to the nature of the Universe, especially at the quantum level.
Raw observations are good, but we need to do more with them. In other words, there must be some form of data analysis. The observations are compared to each other in some fashion (normally some form of mathematical or statistical plot) in order to discover potential patterns, and from that to test different hypotheses.
Collectively, raw observations and analytical results are what we call evidence. We use this evidence to infer what is happening; that is, evidence is used to get to conclusions.
After observing some phenomenon, a pattern often emerges. We can state this pattern formally as an hypothesis. Thus, contrary to its colloquial use, an hypothesis is NOT an "educated guess", but rather "a formal statement of a pattern that appears to exist in a set of observations." In contrast to theories, hypotheses are primarily about the pattern itself, not about an explanation of the pattern.
Unfortunately, humans cannot help but see patterns: castles in the clouds, faces in random objects, "lucky streaks" in games, etc. Not all perceived patterns are real! So to evaluate whether a pattern that we perceive (an hypothesis) might be true, we must test it. We refer to this as "submitting it to falsification": subjecting the hypothesis to some evaluation where it could in principle be shown to be incorrect. Not all hypotheses are falsifiable (synonym: testable): some are purely subjective (e.g., "chocolate is better than vanilla") or involve metaphysical qualities or entities which cannot be measured (e.g., "true justice is superior to true wisdom"). We might hold these as important concepts, but they are outside Science. Indeed, to paraphrase the late philosopher Christopher Hitchens, "What can be asserted without evidence can be dismissed without evidence".
Other hypotheses can be potentially falsifiable with total knowledge of the universe, but we are currently [and perhaps forever] incapable of evaluating (e.g., "the flesh of eurypterids ('water scorpions', extinct for 252 million years) is an effective cure for athletes foot"). Ideas of this second sort are speculations: nothing wrong with them as such, but they aren't particularly useful.
Even good scientific hypotheses remain mere speculations until submitted to a test (often called an experiment). An experiment (i.e., a test of falsification) must be constructed in such a way that the hypothesis could yield observations that demonstrate that the hypothesis is false. For example, we can speculate that "my horse can outrun any horse in the world." However, until we gather evidence to test it, we won't know if this is actually the case (no matter how much we want to believe it.) A rather simple experiment for this: a horse race. If another horse outraces it, then the hypothesis is falsified.
This procedure is called the "hypothetico-deductive method", and is basically what experiments in Science are all about. To put it in its basic form "If you were wrong, how would you know it?"
Note that part of developing a good experimental design is actually phrasing your hypothesis properly. For example, we might be interested in the presence of fossils of ceratopsids (horned dinosaurs, like Triceratops) in rocks the last 15 million years of the Cretaceous Period in continental Africa. If we state our hypothesis "there were latest Cretaceous African ceratopsids", then how many observations do we need to make to demonstrate this is true? Does a single observation with negative results show us there is no ceratopsids in latest Cretaceous Africa? No. How about ten negative results? A thousand? Until we have excavated all latest Cretaceous rocks from Africa, we cannot demonstrate that there are no ceratopsids. However, by stating the hypothesis as "there were no ceratopsids in latest Cretaceous Africa", then a single positive observation of a ceratopsian is all we need to confidently overturn (falsify) this hypothesis.
The above is an example of employing a null hypothesis. The null represents a form of the hypothesis that must be rejected before we even accept a phenomenon exists. If we cannot reject the null hypothesis, there is no reason to think that the phenomenon in question is worth considering. If, instead, we find we can reject the null (in the instance above, finding a latest Cretaceous ceratopsid in Africa), than we can go on and examine the situation in more detail.
The hypothetico-deductive method shows that we can confidently reject hypotheses, but that we cannot "prove" them in an absolute philosophical sense. As the number of observations and experiments which fail to reject an hypothesis increases, we can be more and more confident in its truth. However, ideas in Science are only provisionally accepted: that is, we often use statistical measures of confidence (plus/minus readings, error bars, and other demonstrators of degree of support). Uncertainty is a staple part of Science. However, some ideas are so overwhelmingly well-supported that to reject them at present is perverse: these are what we call "facts". (Similarly - using the example above - if we made many excavations in latest Cretaceous continental African rocks and continuously failed to uncover ceratopsid fossils but find plenty of other dinosaurs, we will provisionally reject the idea of African horned dinosaurs, but recognize that a single fossil could overturn this rejection.)
The following (from Thomas Kida's Don't Believe Everything You Think) are a useful set of characteristics for thinking like a scientist:
- Keep an open mind, but be skeptical of any unsubstantiated claim
- Make sure a claim (hypothesis) can be tested
- Evaluate the quality of the evidence for a claim
- Try to falsify the hypothesis (i.e., look for discomfirming evidence)
- Observations of natural phenomena lead to possible explanations (hypotheses)
- These hypotheses must be falsifiable (i.e., there must be some test, experiment, or observation which can demonstrate that the hypothesis is untrue)
- Until the hypothesis is tested, it is only considered a speculation
- If the hypothesis survives a test (or tests) of falsification, it is tentatively (or provisionally) accepted (keeping in mind that additional tests might potentially overturn the hypothesis)
- Consider alternative explanations (we call these "multiple working hypotheses")
- Other things being equal, choose the claim that is the simplest explanation for the phenomenon (i.e., the one that requires the fewest assumptions)
- This is formally known as the principle of parsimony, and also called Occam's razor
- Other things being equal, choose the claim that doesn't conflict with well-established knowledge
- This is sometimes referred to as the principle of consilience
- Proportion your acceptance of a claim to the amount of evidence for or against a claim
Historical Sciences
Something worth noting concerning the issue of paleontology, historical geology, evolutionary biology, astronomy, and other sciences which are concerned primarily with events which have already happened: i.e., historical sciences. These are concerned with actual particular events and cases just as much as general patterns (as opposed to, say, particle physics or organic chemistry, where all collisions of the same particles or folding of the same proteins are identical). As a consequence, although we can perform some kinds of experiments or observations under controlled circumstances to duplicate the past conditions, in general we are looking at evidence of the past event.
That doesn't make it any less scientific, nor does it dismiss the ability to do repeatable observations. "Repeatability" in this case is where different observers--or the same observer in multiple different examinations--can make the same observations of the same set of data. (For example, if a scientist asserts that a particular layer of clay shows an enriched abundance of the metal iridium, consistent with an asteroid impact, other scientists can sample the same layer and look for this material, and the original research can resample the material to test that it is there.)
There is a cliché that paleontologists are a kind of "detective", and that isn't a bad comparison. Much like forensics experts in crime scene investigations or medical examiners, we examine a series of data to develop a hypothesis (or multiple hypotheses) to explain the observations at hand, and test these hypotheses against both the currently-known data and additional relevant data we look for.