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Empirical research is research that derives its' data by means of direct observation or experiment, such research is used to answer a question or test a hypothesis, i.e. does something such as a type of medical treatment work? The results are based upon actual evidence as opposed to theory or conjecture, as such they can be replicated in follow-up studies. Empirical research articles are published in peer-reviewed journals. Such research may also be conducted according to hypothetico-deductive procedures, such as those developed from the work of R. A. Fisher.

[edit] Terminology

The term empirical was originally used to refer to certain ancient Greek practitioners of medicine who rejected adherence to the dogmatic doctrines of the day, prefering instead to rely on the observation of phenomena as perceived in experience. Later empiricism refered to a theory of knowledge in philosophy which adheres to the principle that knowledge arises from experience and evidence gathered specifically using the senses. In scientific use the term empirical refers to the gathering of data using only evidence that is observable by the senses or in some cases using calibrated scientific instruments. What early philosophers described as empiricist and empirical research have in common is the dependence on observable data to formulate and test theories and come to conclusions.

[edit] Usage

The researcher attempts to describe accurately the interaction between the instrument (or the human senses) and the entity being observed. If instrumentation is involved, the researcher is expected to calibrate his/her instrument by applying it to known standard objects and documenting the results before applying it to unknown objects.

In practice, the accumulation of evidence for or against any particular theory involves planned research designs for the collection of empirical data, and academic rigor plays a large part of judging the merits of research design. Several typographies for such designs have been suggested, one of the most popular of which comes from Campbell and Stanley (1963). They are responsible for popularizing the widely cited distinction among pre-experimental, experimental, and quasi-experimental designs and are staunch advocates of the central role of randomized experiments in educational research.

[edit] Scientific research

Accurate analysis of data using standardized statistical methods in scientific studies is critical to determining the validity of empirical research. Statistical formulas such as regression, uncertainty coefficient, t-test, chi square, and various types of ANOVA (analyses of variance) are fundamental to forming logical, valid conclusions. If empirical data reach significance under the appropriate statistical formula, the research hypothesis is supported. If not, the null hypothesis is supported (or, more correctly, not rejected), meaning no effect of the independent variable(s) was observed on the dependent variable(s).

It is important to understand that the outcome of empirical research using statistical hypothesis testing is never proof. It can only support a hypothesis, reject it, or do neither. These methods yield only probabilities.

Among scientific researchers, empirical evidence (as distinct from empirical research) refers to objective evidence that appears the same regardless of the observer. For example, a thermometer will not display different temperatures for each individual who observes it. Temperature, as measured by an accurate, well calibrated thermometer, is empirical evidence. By contrast, non-empirical evidence is subjective, depending on the observer. Following the previous example, observer A might truthfully report that a room is warm, while observer B might truthfully report that the same room is cool, though both observe the same reading on the thermometer. The use of empirical evidence negates this effect of personal (i.e., subjective) experience.

Ideally, empirical research yields empirical evidence, which can then be analyzed for statistical significance or reported in its raw form.

[edit] Empirical cycle

Empirical cycle according to A.D. de Groot

A.D. de Groot's empirical cycle:
Observation: The collecting and organisation of empirical facts; Forming hypotheses.
Induction: Formulating hypotheses.
Deduction: Deducting consequenses of hypotheses as testable predictions.
Testing: Testing the hypotheses with new empirical material.
Evaluation: Evaluating the outcome of testing.

[edit] See also

• Empirical
• Scientific method

[edit] External links

• Some Key Concepts for the Design and Review of Empirical Research

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