Falsifiability

Definition:

Falsifiability — A statement/claim/hypothesis is falsifiable if it is possible to disprove it. If a theory cannot be falsified, then there is no point even looking examining evidence.

The natural tendency is to put forward a hypothesis and look for evidence to confirm it or induce conclusions from observational data.

Falsifiability is looking at it the other way around, looking for examples that contradict the theory. If the theory resists multiple attempts at contradiction, it’s a good working hypothesis of truth.

Example:

Ask the question “What would be an example of something that, if observed, would contradict the hypothesis?”

Hypothesis — All swans are white

Traditional Approach — Look for white swans to confirm that swans are white

Falsifiability Approach — Look for non-white swans to disprove the hypothesis. (i.e., finding one black nullifies the hypothesis that all swans are white)

Why is it important: 

Using the falsifiability approach provides a more comprehensive understanding of how to structure and run experiments. Although falsifiability is not universally accepted and it has its critics, the concept is still a foundation of most modern scientific experiments.

Karl Popper is credited with disseminating falsificationism as a philosophy of science in the mid 20th century. Popper’s view on science was guided by his use of formal logic. Since there was no way to arrive at the undeniability of a conclusion through induction (going from particulars to a more general principles), Popper theorized that the answer lie in using deductive reasoning (arriving at particular through general principles) and falsifiability. That is, we can always use negative evidence to contradict a statement, but positive evidence does not lead to the conclusion that the general case is always true.

“A million successful experiments cannot prove a theory correct, but one failed experiment can prove a theory wrong.” – Karl Popper

Applications:

Falsifiability is applicable in any area seeking knowledge or truth through empirical evidence.

Science

Most scientific tests today are based on the falsifiability principle.

Personal Life: 

Instead of looking for signs that someone loves you, look for signs that they don’t.

Sources & Suggested Reading:

Occam’s Razor or Principle of Parsimony

Definition:

Occam’s razor is a problem solving principle that states that among competing hypothesis the simpler explanation is more likely to be true. That is, a hypothesis with fewer assumptions is preferable to others if they have the same predictive capability.

The term ‘razor’ refers to shaving away unnecessary assumptions or cutting apart two similar conclusions.

Example:

If you lost your wallet do you assume that (1) you misplaced it or (2) goblins stole it?

Occam’s razor implies that it is much more likely that you misplaced your wallet. In fact that another entity other than you was involved in the action (regardless of whether it was goblins or your sister) is enough to invoke Occam’s Razor. So next time you lose something, jump to the most likely culprit — you. The simplest explanation wins.

Occam’s razor is also commonly illustrated in the adage, “when you hear hoofbeats behind you, think horses, not zebras.”

Why is it important?

Occam’s Razor underlies most scientific undertakings and theory building.

The principle is particularly important because of the undetermination problem which states that for a given set of data there is always an infinite number of possible models to explain it. In a classic example from mathematics, you can draw an infinite number of lines through two points on a plain. Occam’s Razor could be invoked to state that it is more likely that this line is straight than that it has 1000 inflection points. It is important to understand underdetermination because it is at the root of many common mental fallacies — that a theory fits all the data points doesn’t mean it is correct. There are several situations where more than one theory fits the data (as in our Goblin’s example above) and Occam’s razor helps us to isolate the theories which are more likely to be true, if not only because of statistical probability (a statement with one proposition has a higher likelihood than a statement with many propositions). This isn’t to say that complex theories never win the day, just that is more likely that the simplest explanation is correct.

If thought through in this sense, Occam’s Razor is particularly important when seeking to apply our lattice work of mental models. If there are two competing mental models that lead to the same result, we should apply the simpler one, minimizes cognitive load and increasing the probability that our outcome is correct.

Some people equate Occam’s razor to the KISS (keep it simple, stupid) principle, but that is, for lack of better words, stupid. Simplicity isn’t preferable over complexity just to avoid the problems with complex models. Occam’s razor simply states that if two models exist that have the same predictive capability, the simplest model is preferred. That is, you should always prefer the simplest model only if they have the same explanatory power.

Occam’s razor is most relevant to universal models such as those in systems theory, mathematics, or philosophy. If the foundations of universal models are unnecessarily complex the chances that we can arrive at manageable models and explanations are slim.

How can you apply it? 

Occam’s razor is often considered one of the fundamental tenants in modern science and can be applied in a myriad of fields including, but not limited to, physics, biology, medicine, statistics, religion, ethics, probability theory, and even to personal situations.

In medicine, for example, Occam’s razor is also known as diagnostic parsimony. Diagnostic parsimony advocates that doctors should look for the least possible causes that account for all symptoms. That being said, it is often more likely that a patient has several common diseases rather than one rare disease responsible for all symptoms. Caution is advised, especially when dealing with outcomes where the loss function is prohibitively high, such as medicine.

There are several papers investigating Occam’s razor in probability theory. In fact, Occam’s razor is intuitively justified through probability as by definition each new assumption introduces additional probably for error.

Occam’s razor is also found in programming and software development. The best programmers are those that utilize less code, and thus computational power, to arrive at similar results. Software solutions increase in complexity as the number of requirements and features increase, however, that does not mean that the number of lines of code has to increase in lockstep. The best developers are those that can reduce complexity as they increase functionality.

The Lean Startup methodology has garnered quite a bit of traction in the startup space and much of it is derived from application of Occam’s razor. A Minimum Viable Product (MVP) is the simplest version of a product that enables a team to collect the maximum amount of validated learning with the least effort. In this sense the Minimum Viable Product is arrived at by applying Occam’s Razor to a startup problem hypothesis. By trimming assumptions startup founders arrive at better MVPs.

Simplicity is the ultimate sophistication

Leonardo da Vinci

The business schools reward difficult complex behaviour more than simple behaviour, but simple behaviour is more effective.

Warren Buffet

Everything should be made as simple as possible, but not simpler.

Albert Einstein