How do scientists analyze empirical evidence?

"Empirical evidence" or "scientific evidence" is evidence which serves the purpose of either supporting or counter a scientific hypothesis or theory.

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The word "empirical" indicate information gained by means of observation, experience, or experiments.

A central theme of science and scientific method is that all evidence must be empirical, or at least empirically based, that is, it should depend on evidence or results that can be observed by our senses. It should be noted here that scientific statements are subject to and derived from our experience or observations and empirical data is based on both observations and experiment results.

In the process of accepting or disproving any hypothesis, facts (evidence) are coupled with inference which is the act of deriving a conclusion on the basis of observations or experiment.

However, scientific evidence or empirical evidence is evidence where evidence does depend on inference thus it enables other researchers to examine the assumptions or hypothesis employed to see if facts are relevant at all to the support of or counter the hypothesis.

For example, an infective organism, "Helicobacter pylori", has shown to cause stomach ulcers in humans. Following evidence may prove the hypothesis that H. pylorus is indeed a cause of peptic ulcers in humans.

• If someone voluntarily ingests H. pylori, it results in chronic gastritis
• Experimental challenge to animals stimulates human infection and gastritis
• Proper antimicrobial therapy in patients clears infection and thus clears gastritis
• The H. pylori only found in gastric epithelium
• There is a systemic immune response seen in patients with H. pylori infection
• Antibodies against H. pylori disappears after successful antimicrobial therapy

Let's take another example of global warming which remains an ongoing dispute about the effects of humans on global climate. You may hear following evidence in favor or theory of global warming:

• Graphs of historical trends show increasingly warming temperature
• The levels of carbon dioxide gas are on the rise in atmosphere
• The levels of methane are also rising
• We are seen more frequent extreme weather as never before
• Glaciers are disappearing rapidly
• Arctic sea ice is melting
• Antarctic sea ice is also melting
• Greenland's ice sheet is also melting
• Incidence of tropical diseases is on the rise
• Oceans are warming with Coral bleaching and disintegration

No hypothesis or theory can be called scientific or accepted if it lacks empirical evidence in favor. Therefore, empirical evidence can be use both to accept or counter any scientific hypothesis or theory.

What is empirical evidence?

Definition and explanation

Empirical evidence is the evidence that we directly observe and get from our senses. This might be contrasted to philosophical or theoretical reasoning, which can be done without any direct observation of ‘real life’.

Empirical evidence is related to the philosophical distinction between a priori and a posteriori reasoning. A priori reasoning, that is, without (or ‘prior’ to) evidence or experience is the sort of reasoning commonly used by logicians, philosophers, and mathematicians. a posteriori reasoning is based on observation and empirical evidence.

In science

Let’s take a look at an empirical evidence example from the healthcare industry.

Imagine that you are a doctor and that you are interested in lowering blood pressure as a way to reduce the probability of having a heart attack. 

You hear about a new drug called atenolol that slows down the heart and reduces blood pressure.

You use a priori reasoning to create a hypothesis that this drug might reduce the risk of a heart attack because it lowers blood pressure.

But in this scenario you don’t just rely on a priori reasoning. You want to obtain empirical evidence for your hypothesis.

So you run a large randomized drug trial. You give a sugar-pill placebo to some people and atenolol to the others. It turns out that the drug indeed reduces the blood pressure of people who take it.

Now you have empirical evidence that atenolol reduces blood pressure, but what about the risk of a heart attack?

When you analyze the dataset, you see that it doesn’t reduce mortality by as much as other drugs that have a similar effect on blood pressure.

So your a priori reasoning that this drug would reduce the risk of a heart attack by lowering blood pressure was invalidated by a posteriori empirical evidence.

Empirical evidence vs theoretical evidence

As the name suggests, empirical evidence isn’t the only sort of evidence that can support our beliefs; while empirical evidence is great, we can also form sensible beliefs about things through theoretical reasoning. 

Take for example the recent COVID vaccines that have been in development and trial around the world. While running trials on the vaccine and gathering that empirical evidence of its effectiveness is absolutely crucial, some people say that before the trial concludes we have ‘no data’ and so can’t say anything about (for example) how effective the vaccine might be.

Before a vaccine trial is conducted it's true that we don’t have empirical data yet on how likely it is to work, but we can still form useful beliefs about it. For example, we might use ‘reference class forecasting’ to look at the fraction of all vaccine trials in history that had positive results, and use that to inform our beliefs about how likely the COVID vaccine is to work.

Scientists also have a theoretical understanding of how the vaccine works causally. Although we have ‘no data’ on whether the vaccine will still work if given by a person dressed in a Santa Claus outfit (we didn’t run that in the trial!), we understand the causal mechanism behind the vaccine and so we can safely assume that if it works, it will also work when given by a person in a Santa outfit.

There are some important questions that we can’t wait around to gather empirical evidence for, such as the possibility of nuclear war between Russia and the US, or the likelihood that we’re living in a simulation. We can’t wait for there to be a nuclear war before we can tell anything about its probability! For those questions, we have to bolster our empirical faculties with theoretical reasoning.

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