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Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of professional scientific research. A Lancet review on Handling of Scientific Misconduct in Scandinavian countries gave examples of policy definitions. In Denmark, scientific misconduct is defined as "intention[al ...
Scientific misconduct is the violation of the standard codes of scholarly conduct and ethical behavior in the publication of professional scientific research. It is violation of scientific integrity: violation of the scientific method and of research ethics in science, including in the design, conduct, and reporting of research.
An example of a data-integrity mechanism is the parent-and-child relationship of related records. If a parent record owns one or more related child records all of the referential integrity processes are handled by the database itself, which automatically ensures the accuracy and integrity of the data so that no child record can exist without a parent (also called being orphaned) and that no ...
Research integrity or scientific integrity is an aspect of research ethics that deals with best practice or rules of professional practice of scientists. First introduced in the 19th century by Charles Babbage , the concept of research integrity came to the fore in the late 1970s.
It is the violation of scientific integrity: violation of the scientific method and of research ethics in science, including in the design, conduct, and reporting of research. A Lancet review on Handling of Scientific Misconduct in Scandinavian countries provides the following sample definitions, [ 12 ] reproduced in The COPE report 1999: [ 13 ]
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical and social sciences, humanities, [2] and business ...
In scientific inquiry and academic research, data fabrication is the intentional misrepresentation of research results. As with other forms of scientific misconduct, it is the intent to deceive that marks fabrication as unethical, and thus different from scientists deceiving themselves. There are many ways data can be fabricated.
Data manipulation is a serious issue/consideration in the most honest of statistical analyses. Outliers, missing data and non-normality can all adversely affect the validity of statistical analysis. It is appropriate to study the data and repair real problems before analysis begins.