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Empirical Evidence: A Definition

Empirical evidence is information that is acquired by observation or experimentation. This data is recorded and analyzed by scientists and is a central process as part of the scientific method.

The scientific method begins with scientists forming questions and then acquiring the knowledge to either support or disprove a specific theory. That is where the collection of empirical data comes into play.

Before any piece of empirical data is collected, scientists carefully design their research methods to ensure the accuracy, quality and integrity of the data. If there are flaws in the way that empirical data is collected, the research will not be considered valid.

The scientific method often involves lab experiments that are repeated over and over, and these experiments result in quantitative data—in the form of numbers and statistics. However, that is not the only process used for gathering information to support or refute a theory. Qualitative research, often used in the social sciences, examines the reasons behind human behavior.

The objective of science is that all empirical data that has been gathered through observation, experience and experimentation is without bias. The strength of any scientific research depends on the ability to gather and analyze empirical data in the most unbiased and controlled fashion possible. However, in the 1960s, scientific historian and philosopher Thomas Kuhn promoted the idea that scientists can be influenced by prior beliefs and experiences.

Because scientists are human and prone to error, empirical data is often gathered by multiple scientists who independently replicate experiments. This also guards against scientists who unconsciously, or in rare cases consciously, veer from the prescribed research parameters which could skew the results.

The recording of empirical data is also crucial to the scientific methods, as science can only be advanced if data is shared and analyzed. Peer review of empirical data is essential to protect against bad science.

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