Assignment:

Based on your own experience as well as the readings so far, how would you explain falsifiability and the contingency of scientific conclusions, and to what extent do you think they should be understood as reliable explanations of how the world works?

Below is this weeks lesson. The finished assignment must contain elements of this weeks lesson.

LESSON 2

Methodology of Science

LESSON TOPICS

  • Methodology
  • Francis Bacon
  • Galileo
  • Deduction and Induction
  • Deduction and Induction: Example
  • Complications of the Scientific Method
  • What Science Is…and What it is Not!

INTRODUCTION

Welcome to Week 2: Methodology of Science. In this lesson, we will continue our study of the philosophy of science by focusing on how science does what it does.

In our last lesson, we grappled with the question, “What is Science?” and its corollary, “What is not Science?” In this lesson, we are going to define the scientific method. For the organized, Type A personalities in the class, this will be like a breath of fresh air! Bacon is the kind of guy you’d invite over for supper and he’d carefully line up his shoes and umbrella by the door before he’d walk to the dining room. For the freethinking artistic types in the class, this lesson will give you some insight into how a little bit of order might be a good thing.

This week’s readings and discussion will look at Bacon’s scientific method and the ways in which it has been theorized, explained, developed, contradicted, and modified over the last 400 years.

The Scientific Method made easy

5 STEPS:

(1) Observation: What do you keep seeing?

(2) Hypothesis formation: Ask “why is that happening?” and make your best guess. The guess is the hypothesis. The next step is to design an experiment to confirm or disconfirm the hypothesis.

(3) Experiment: Poorly designed experiments give results that you can’t trust. A well designed experiment gives data that leads to a trustworthy conclusion.

(4) Conclusion: Explaining what the data mean requires pattern recognition. The conclusions of many experiments can be used to generalize, leading to the last and philosophically creative step, i.e. theory creation.

(5) Theory: The story that explains the conclusion and generalizes over other many cases. Sometimes we call the theory a ‘formula’ (like E=mc2).

Methodology

The scientific method is a series of steps that are usually done sequentially starting with defining a research question or, even more simply, with identifying something that makes us curious to know more.

DEFINE QUESTION

The scientist notices something she finds interesting or perplexing and defines a research question based on this initial curiosity.

GATHER INFORMATION

Do some thinking on the subject. Bring in knowledge from personal experience, further informal observation, and reading existing literature on the subject. This might result in redefining or clarifying the research question

FORM HYPOTHESIS

Tentatively answer the question based on observation and initial research. Predict the likely results of the experiment. Essentially, the experiment would be testing whether the hypothesis is correct.

TEST HYPOTHESIS

Design and conduct an experiment that will directly test the correctness of the hypothesis.

ANALYZE DATA

Pull the numbers, measurements, and other data from the experiment and pull it all together into a format that makes sense.

INTERPRET DATA

Evaluate the significance and relevance of the data. Does the data prove or disprove the hypothesis?

PUBLISH RESULTS

Write out the conclusions of the experiment and what was learned. Share the results so that everyone can learn something from the information.

RETEST

Often, scientists repeat the same experiment or tweak the research question and approach from a new angle.

Francis Bacon

These versions of the scientific method derive from the work of Francis Bacon, whose Novum Organum (translated as “the new instrument”) argued that scientists must ground their work in experience and observation rather than pure deductive logic. To summarize (and radically simplify) Bacon, the problem with logic as practiced by Plato and Aristotle is that valid arguments can be constructed based on incorrect premises, and there is no logical way to disprove those incorrect premises. Bacon called for a new approach, particularly in the natural sciences (or “natural philosophy,” as he termed it), based on observation, experimentation, and induction. The outline he provides in the Novum Organum often receives credit as the foundation of the scientific method frequently taught today.

When presented in this way, the scientific method purports to explain scientific epistemology, or, to use the subtitle of an article on teaching physics, “how scientists know what they know” (Wenning). A famous story illustrates the method by how Galileo proved that all objects fall at a consistent rate of acceleration, regardless of weight.

Galileo

Galileo was a great scientist and philosopher. Back in the Renaissance, he had this idea that a lighter object would fall at the same rate of acceleration as a heavier object. This flew in the face of the conventional wisdom of the day that argued (based on Aristotle’s theories) that a heavier object would fall to earth more quickly than a lighter object. Galileo was curious, so the story goes that he took balls of different weights to the Leaning Tower of Pisa and dropped them off to the side.

Aristotle hypothesized the common-sense idea that heavier objects will fall to earth more quickly than lighter objects. Galileo disagreed, and predicted that if the acceleration of gravity affects objects differently depending on their weight, two balls of different weight dropped from the top of the Leaning Tower of Pisa should hit the ground at the same time. If gravity is constant for all objects, however, the two balls would strike simultaneously. Performing the experiment showed that Aristotle was wrong and Galileo was right: the balls did fall at the same rate of acceleration. Galileo’s became the accepted model, which itself was subject to further testing. Newton’s Law of Gravity extended Galileo’s theory to cases further from Earth (such as the orbit of the Moon and other planets) and quantified it in mathematical terms. Galileo’s observations and Newton’s Law remained the best explanations of gravity until Einstein’s General Relativity provided a more precise explanation in 1915.

The remainder of this lesson will look more closely at Bacon’s inductive methodology and how it differs from classical deductive logic before examining some of the problems—both philosophical and practical—that arise from attempts to adhere strictly to a Baconian scientific method when describing and defining science.

Tools of science

It should be noted that math and logic are tools used in science, not science-proper.

Most scientific reasoning is inductive. This means that the conclusions science comes to are probabilistic. When we say that a theory is “confirmed”, we mean that it has a “high probability” of being correct, rather than proven. Nothing in science has 100% certainty, so we try to stay away from that word.

As you’ll see in the readings on “falsifiability”, science approaches things backwards. As evidence mounts in favor of a theory, we then look for ways to disprove it, rather than prove it. If we can’t disprove it, then it is a good one. Although we can never “prove” a theory beyond a shadow of doubt, we can disprove a theory, and do it with only one counter-example.

Here is an example. Imagine you are investigating a murder. You interview neighbors who say Smith always hated Jones and repeatedly said he wanted to kill him (weak circumstantial evidence). So, you begin compiling evidence for the hypothesis that Smith killed Jones and try to disprove (not prove) it. You find Smith’s fingerprints on the knife in Jones’s back (beginning to look like “he done it”, but not enough evidence yet). Then you find DNA evidence at the scene (looking bad for Smith). Notice, this is still not absolute proof that Smith killed Jones. So far you have only found confirming evidence, but no disconfirming evidence, so this would normally be enough to convict Smith of the murder, until… you get another piece of evidence that disproves your original hypothesis, i.e. that Smith is paraplegic and can’t move from the neck down. He couldn’t have done it! He was set up. And that’s why we say you can never prove things, only disprove them.

Deduction and Induction

Inductive reasoning, as hinted at above, can actually be rather difficult to explain directly. The most helpful way to approach it is by comparing it to deductive reasoning, which is sometimes (inaccurately) viewed as its opposite.

Deductive reasoning is the process of moving from general information or principles to a specific conclusion. The classic version of deduction is the syllogism: if X is true, and Y is true, then a certain conclusion can (and must) be drawn.

  • Major Premise: All men are mortal.
  • Minor Premise: Socrates is a man.
  • Conclusion: Therefore, Socrates is mortal.

The mathematical version of this is the transitive property: If A = B, and C = A, then C = B.

Deductive logic provides absolute certainty: If statements 1 and 2 are true, statement 3 must also be true. The problem, as Bacon points out and Galileo demonstrated in his falling objects experiment, is that if either statement 1 or statement 2 is false, a logically valid conclusion to the syllogism will be false as well.

Consider this example:

  • All pies are delicious.
  • A mud pie is a pie.
  • Therefore, a mud pie is delicious.

In this case, while statement 3 is the necessary conclusion of the first two statements, neither statement 1 nor statement 2 is true. So, while the reasoning is valid, the conclusion is false. Deduction is only as good as its premises, and any error in the premises produces an incorrect conclusion.

Bacon put it this way in Aphorism XIV: “The syllogism consists of propositions, propositions consist of words, and words are symbols of notions. Therefore if the notions themselves (which is the root of the matter) are confused and over-hastily abstracted from the facts, there can be no firmness in the superstructure. Our only hope, therefore, lies in a true induction.”

In order to avoid this problem, Bacon argued that a different kind of reasoning needs to be applied in order to determine the truth of the initial premises. Rather than beginning with general principles and deriving a specific conclusion from them, we should observe and collect specific instances, from which we can infer more general principles. This is inductive reasoning, which moves from the specific to the general by observing patterns in the past and projecting those patterns onto future instances.

Deduction and Induction: Example

Using our pie syllogism as an example, we begin by collecting data about pies by sampling as many as we can. Yum! All in the name of science…

If each pie we try is delicious, we can reasonably predict that the next pie we eat will also be delicious, and we might infer the principle that all pies are delicious. However, this prediction is based on a reasonable extrapolation, based on our experience, rather than any certainty. When we taste the mud pie, we only infer or predict that it will be delicious—it does not have to be. The inductive version of the pie argument looks more like this:

  • All of the pies we have tasted so far are delicious.
  • A mud pie is a pie.
  • Therefore, a mud pie is probably delicious.

Once we taste the mud pie and discover it is not, in fact, delicious, we must return to our initial premises and revise them. Either all pies are not delicious, or a mud pie is not really a pie. Science follows this inductive methodology.

The logical problem of induction is that it is impossible to prove that inductive reasoning will ever lead to correct, valid conclusions. “The problem is how to support or justify them and it leads to a dilemma: the principle cannot be proved deductively, for it is contingent, and only necessary truths can be proved deductively. Nor can it be supported inductively—by arguing that it has always or usually been reliable in the past—for that would beg the question by assuming just what is to be proved” (Vickers).

This is the difficulty that Godfrey-Smith explains in Chapters 3 and 4 of Theory and Reality, where both the Logical Positivists and Karl Popper try to explain how we know that the scientific method produces an accurate picture of the world and how it works.

Complications of the Scientific Method

As this week’s readings make clear, the Problem of Induction is a longstanding and thorny philosophical question, but it is not the only issue that complicates our investigation of scientific methodology and epistemology. When we examine science in practice, we find that the inductive method outlined by Bacon and multitudes of science teachers do not, in fact, accurately represent what scientists do. We imagine a lone scientist conducting experiments in his laboratory, whether a sober figure in a white lab coat, or a deranged Dr. Frankenstein but neither vision is particularly accurate. As philosophers of science and practicing scientists have long acknowledged, actual science is far more complicated than either picture suggests.

Much like the logical constructions that Bacon critiqued, the traditional model of the scientific method does not always hold up well when we examine what practicing scientists actually do. Donald Simanek, a retired physics professor who maintains a respected website on science and pseudoscience, calls these step-by-step directions “misleading.” The description he provides of science in action accords more closely with Bacon’s proposed methodology than the schematic version of the method in these illustrations, as well as with Popper’s advocacy of falsifiability and skepticism as key requirements of valid science:

Even when a model survives such testing we should only grant it “provisional” acceptance. In the future, cleverer people with more sophisticated measuring techniques and a more advanced scientific conceptual framework may expose deficiencies of the model that we didn’t notice. (Simanek)

Thus, Aristotle’s model was accepted for over one thousand years until Galileo falsified it; Newton’s work confirmed and expanded Galileo’s. Newton’s Law remained the accepted model for over 300 years. After Einstein, Newton’s model is now accepted as approximately correct or “incomplete” (Knop)—it works well enough for most instances, from baseball pitches to rocket science. Much like scientific models and theories, the “scientific method” in its simple, step-by-step version, is an incomplete model of how science works, which should be accepted only as an approximation.

WHAT SCIENCE IS

Science is:

  • Messy! It’s flexible and multifaceted, adapting to changing information and ideas.
  • A community effort! Scientists collaborate with each other. They also review, corroborate, and challenge each other’s work.
  • Creative and Innovative! It’s about exploring and discovering.
  • An ongoing process! It raises as many questions as it answers, and all answers are contingent and open to revision as new evidence is considered.

WHAT SCIENCE IS NOT

Science is Not:

  • A linear, step-by-step process.
  • The product of individuals working in isolation.
  • A rigid set of rules to follow.
  • About drawing definite conclusions.

Philosophers of science must, therefore, expand their theories of scientific epistemology—how scientists know what they know—to account for these other factors. Bacon’s inductive method is a starting point for understanding scientific methodology and thinking, but as so much in science, it provides an incomplete picture.

Take, for instance, the question of experimental testing of hypotheses. We already looked at Galileo’s famous experiment with falling objects at the Leaning Tower of Pisa as a classic example of the scientific method at work. But is it?

First and foremost, we do not even know that he ever performed the experiment at all! While Lienhard gives some circumstantial evidence that Galileo did drop objects from the tower, we have no direct testimony to this. Galileo describes the experiment in hypothetical terms in his treatise “On Motion” (van Helden).

Likewise, many of Einstein’s experiments in relativity and gravity were also “thought experiments”: exercises in the imagination used to test scientific theories or principles without actually, physically performing those experiments.

Besides Galileo’s Falling Objects and Einstein’s elevator, other famous thought experiments include Maxwell’s Demon and Schrödinger’s Cat. But if all these scientists (and many others!) have done is thought about what might happen, given certain assumptions and knowledge of the way the world works, how can they be said to have performed an experiment at all? Yet, thought experiments have formed an important part of the scientific methodology for centuries and, as these examples illustrate, have often played a part in significant scientific breakthroughs.

Conclusion

We’ve covered a lot of ground in this lesson! Scientific methodology, deduction, induction, falling objects, and mud pies…

Philosophy of science may have begun with a grounding in apparently clear, straightforward empiricism and induction, but it has also grown to address the reality of science as a highly productive and inherently messy, ongoing process. We will examine several schools of philosophical thought in future lessons, beginning with a closer look at the Logical Positivists and empiricism.

References

Bacon, Francis. Excerpts from Novum OrganumEarly Readings in the Philosophy of Science. Ed. Sarah Canfield Fuller. Charles Town, WV: APUS ePress, 2013. Web.

Brown, James Robert, and Yiftach Fehige. “Thought Experiments.” The Stanford Encyclopedia of Philosophy (Fall 2011 Edition). Ed. Edward N. Zalta. Web.

“Einstein Thought Experiments.” Nova. WGBH. 9 Sep. 1997. Web.

Falk, Dan. “Galileo’s ‘Falling Bodies’ Experiment Re-Created at Pisa.” Dan Falk Science. 12 Oct. 2009. Web.

“How Science Works.” Understanding Science. University of California Museum of Paleontology. 3 January 2013. Web.

Klein, Jürgen, “Francis Bacon”, The Stanford Encyclopedia of Philosophy (Winter 2012 Edition), Edward N. Zalta (ed.), URL = <http://plato.stanford.edu/archives/win2012/entries/francis-bacon/>.

Knop, Rob. “Kepler, Newton, and Einstein: ‘Wrong’ Theories and the Progress of Science.” Astronomy Seminar of the Week. 16 Sep. 2012. Web.

Lienhard, John. “Galileo’s Experiment.” Engines of Our Ingenuity 166. University of Houston. Web.

—. “Schrodinger’s Cat.” Engines of Our Ingenuity 347. University of Houston. Web.

“The Scientific Method.” Science Made Simple. Web.

Pössel, Markus. “The Elevator, the Rocket, and Gravity: The Equivalence Principle.” Einstein Online Vol. 1 (2005): 1009. Web.

Simanek, Donald E. “The Scientific Method.” Web.

Thomson, William (Lord Kelvin). “The Sorting Demon of Maxwell.” 1874. The Kelvin Library. Web.

Van Helden, Albert. “On Motion.” The Galileo Project. 1995. Web.

Vickers, John. “The Problem of Induction.” The Stanford Encyclopedia of Philosophy (Spring 2013 Edition), Edward N. Zalta (ed.), Web.

Wenning, Carl J. “Scientific Epistemology: How Scientists Know What They Know.” Journal of Physics Teacher Education 5.2 (2009): 3-15. Web.

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