The short answer is no. Read on.

A formal proof is a sequence of sentences, starting from axioms, and developing using rules of inferences. Details are here: http://en.wikipedia.org/wiki/Formal_proof .

An experiment is not a formal proof. A formal proof is *deductive*while an experiment is

*inductive*. Deduction is the method of inference in formal, rigorous models, such as math, computer science, and logic. While induction is the method of inference in observation-based models, such physics, biology, and chimestry (and similar fields). Induction cannot give useful and trustworthy information except if quantified correctly. The usual method of quantifying induction is through statistics (and more recently, machine learning). Experiments are mostly used in applied fields, where it suffices (and is possible) to show that

*something*occurs. However, it is impossible to use experiments to show that something does

*not*occur. In particular, it is impossible to show, using experiments, that a system is secure; since it is equivalent to showing that something bad does

*not*occur.

Explanations are something different. Explanations are just a

*theory*. Some of them may be tested, if they were falsifiable (testable, if you wish). But to the uninitiated, they can be very deceiving. Just because you can

*explain*something, does not mean you proved it. An explanation just shows that something is

*plausible*. But does not show that it is

*unavoidable*. There is a cognitive bias known as

*confirmation bias*(look it up) that say we are more likely to believe things that we can explain; which leads to serious logical fallacies. Therefore, a true scientist (going through masters and PhD) is trained to challenge his believes by trying to

*prove their opposite*. Which is why in statistics we are usually interested in the

*null hypothesis*instead of what we are actually trying to show. However, this is still more related to the inductive branch of inference, not the deductive branch.