What's important about science?  We think the most important aspects of science are

skepticism, empiricism, and rationalism. 

The first refers to an attitude toward beliefs and assumed facts, the second refers to a way of knowing true reality, and the last involves the use of reason in the search for reality.  We'll say more about all of them below. 

These key factors are what makes science important in human existence (including human survival), what people, especially those who doubt, or criticize science, need to take into account.

Human fallibility:

But before we start, we are NOT, we repear NOT saying that science is infallible.  As it happens, a substantial amount of criticism directed at science concerns its fallibility.  So let's address this right off the bat: Science is a human activity. Humans can be fallible. So science can be fallible.

For those who are interested, this is a sort of a logical syllogism: if (a) Humans do science, and (b) Humans can be fallible, then (c) the science can be fallible.

BUT as you will see in the discussion below, scientists know this (that humans can be fallible), which is why they created science, a way of knowing about the world that takes into account human fallibility, particularly in knowing reality, and tries to remedy it over time.

So, as we often do, let's start with a definition:

science (noun):

1. A branch of knowledge or study dealing with a body of facts or truths systematically arranged and showing the operation of general laws: the mathematical sciences.

2. Systematic knowledge of the physical or material world gained through observation and experimentation (i.e., the scientific method).

3.Any of the branches of natural or physical science.

4. Systematized knowledge in general.

5. Knowledge, as of facts or principles; knowledge gained by systematic study.

Epistemology: How we know things.

As you read through these five definitions of science, you'll see the word "knowledge" more than once.  We just thought you'd like to know that this falls under the philosophical topic of epistemology, which is all about how we know things.

Scientific Method: What it boils down to is this: Science is a way for humans to know things about the world around them, what the physical world is comprised of and how it works.  As we'll see below, science employs a method that helps minimize human fallibility and maximum the validity of what we learn from it.  The development of what came to be called "scientific method" has been seen as the basic foundation for what came to be called "science."

Skepticism:

Scientists are all skeptics.  They take nothing for granted and do not rely on beliefs or opinions for finding truth and reality.  To an extent, this means that they approach things with doubt.  This does not mean that they assume all opinions and beliefs are false.  They simply believer they must be verified by observable data.

Reasoning: Skepticism uses our ability to reason, apply critical thinking, collect and analyze observable data to find true reality.  It is a process whereby scientists seek to determine validity of a supported conclusion that arise from well designed research, NOT the process of finding a preconceived conclusion.  This last point is crucial.  Science does everything possible to avoid the fallacy of confirmation bias (seeking to prove what one already believes to be true).

Plato vs. Aristotle

We can trace our approaches to knowing things all the way back to these two ancient Greek philosophers, Plato and Aristotle.

Plato held that pure reason was the path to knowing and truth.

Aristotle, a student of Plato, held that observation was they way.

These two approaches result in empiricism and rationalism.

Empiricism:

This is what we call knowing based on observation.  Science is based on empiricism (the Aristotelian approach), knowing by means of seeing.  Over the years, observation has become more difficult (e.g., in subatomic physics), but science continues to strive toward accurate and valid observation.

Rationalism:

This is the application of reason to what we observe (using the Platonic approach).  Science is also based on rationalism, especially in how we view causality and form theories for explaining how things happen.  Scientists use reason and logic to form their understandings.

Spiritualism:

Science does NOT employ spiritualism.  Science looks to find the laws of nature but not who, or what created those laws.  Science is NOT incompatible with spiritualism, or any set of religious beliefs (except religious beliefs that invalidate science).  There are plenty of scientists who believe in God.

 To see the website for an international organization that deals with the relationships between science and religion. 

Paradigms:

As defined by the Oxford English Dictionary a paradigm is "a typical example or pattern of something; a pattern or model". In an important book about the history of science, The Structure of Scientific Revolutions (published in 1962), Thomas Kuhn defined the term as: "universally recognized scientific achievements that, for a time, provide model problems and solutions for a community of practitioners." 

The once held notion that the Earth is the center of the universe is a paradigm that was eventually abandoned--the paradigm shifted.

Science looks to explore within the context of a paradigm, and further when a paradigm proves less useful, identify new paradigms.

Imagination:

Science DOES use imagination.  In fact, Einstein himself was noted for using his imagination to come up with a
"thought experiment" in his theorizing about relativity.  In order to expand knowledge, it is valuable to imagine different was to look at things (new paradigms-see below).  An hypothesis is an exercise in imagination.

At times, it is imagination that leads to scientific revolutions and paradigm shifts (e.g., the shift from seeing earth as the center of the universe to seeing it as simply a part of the universe).

Facts and Theories:

Elsewhere on this website we discuss the difference between these two (click HERE to see that discussion).  For now, we just want to say that what science observes are facts, which are neither true, nor false, but just facts (.e.g., if you drop a rock, it will fall to the ground--that is a fact.).  Facts are the data scientists seek to discover and explain.

Errors in observation: While the fact, in itself, is neither true, nor false, our perceptions can be true, or false.  That doesn't change the fact as an external, objective reality.  It just means, we haven't truly seen the fact.  These errors can occur as a result of our method for viewing the fact (for example, we use an incorrectly calibrated instrument).  And they can result from internal, mental biases, which we discuss elsewhere on this website.

 To see our introduction to this matter of bias.

Theories offer explanations for those facts that are based on our reasoning, often using cause and effect to arrive at laws of nature.  Theories can be valid, or invalid.  Science continuously seeks to validate various theories, often replacing those that are found invalid (often do to limitations in the theory, that is, things it can't account for) with new theories.  An example would be how the theory of relativity expanded Newtonian mechanics, and then quantum mechanics came to expand or replace both.

Model: Often, scientists use models, both as a preliminary to developing a theory, and as an ongoing method for testing a theory.  So a model is a verbal, mathematical, or visual representation of a scientific structure or process, which allows scientists to construct and test inferences and theories.  Like theories, models can be valid, or invalid.

Crucial Point: Theories and models are all part of how scientists go about developing and sharing our understanding of realities of how the world works.  Of the two, facts and theories, the facts are most important.  If a theory about how the facts function is invalid, that does NOT invalidate the facts.

Scientific Goals:

 There are several things science seeks.  Here are some of the most important:

Prediction

Some might consider this the ultimate goal of science, predicting what can and will happen.  Science seeks to know what causes will lead to what effects in what circumstances.  As mathematic models (often employing probability and a new notion called "fuzzy logic") have become more complex and sophisticated, science looks toward the interaction of multiple causes leading to multiple effects.  A prime example of this would be weather prediction (we're talking about local daily weather, not climate, but it can extend into that area as well).

Accuracy

Remember we mentioned observation above?  Well, the issue here is how accurate are the observations.  Science works constantly to improve accuracy, often by developing new observational techniques (the cloud chamber used to observe subatomic particles is such a technique)

Reliability

In science, reliability has to do with replication.  For something to be reliable, we have to know it will repeat.  For example, for a bridge to be reliable, we have to know we can cross it more than once (usually, many times more).

The more something is replicated in research, the more reliable it is.  Another way of putting it is, reliability results when the same (or highly compatible) results are achieved by same study repeated either over time, or by different researchers, or both.

Validity

Loosely speaking, this refers to truth, how true are the findings of the research.  There are several different types of validity.

Content/Construct Validity: What this looks at is does the research actually study what it says it studied (e.g., Does an IQ test really measure intelligence)?  Were the constructs (these are theoretical concepts) and the contents (design of the study) appropriate to the study?  In other words, doing an experiment about subatomic particles by weighing baseballs is NOT valid.

Internal Validity: Internal validity occurs when it can be concluded that there is a causal relationship between the variables being studied. A danger is that changes might be caused by other factors.  In other words, internal validity means that we have looked at and controlled enough of the variable, both causes and effects, to say that A caused B.  When internal validity is strong, successful replication of the study is very likely.

It is important to note that experimental studies examine causal relationships, but correlational studies do not--they just look at how two, or more things may change together.

External Validity: This occurs when the finding in the study can be generalized to the world at large.  In other words, the findings aren't limited to the laboratory.

Predictive Validity: As noted above, many see this as an ultimate goal.  Scientist consider their research and the theories they use valid when it leads to prediction (e.g., predicting what will happen if dynamite is ignited.  More importantly, prediction can lead to control.  If we can predict an outcome from certain causes, we can possibly create the outcome when we want and need it to happen, OR we may be able to prevent that outcomes by eliminating the causes.

Scientific Consensus:

This occurs when scientists come to a shared finding, either through replicated research (see reliability above), or through replicated analysis of data reported.  To be clear, this consensus is NOT a shared opinion.  It is a shared empirical perception based on repeated research and analysis.

Do scientists always agree?  No, but when they disagree, they have to present factual information and clear description of analytical rationale.  Without these, such a disagreement falls into the realm of opinion.

It is important to understand that science is ultimately a group endeavor, and any factual competition between scientists is of benefit to us all.